Browse Articles

Cell and Gene Therapies — Improving Access and Outcomes for Medicare and Medicaid Beneficiaries

The fault systems that control the occurrences of iron ore deposits in northeastern Aswan, Egypt

Abstract The present study combines remote sensing data (Landsat-8 and ASTER) with structural analysis to identify the fault systems affecting the distribution of the ironstone beds in northeastern Aswan, Egypt. Sedimentary rocks, such as the Abu Aggag, Timsah, and Umm Brammily formations, characterize northeastern Aswan. The Abu Aggag Formation consists of kaolinitic conglomerate, conglomeratic sandstone, and mudstone. The upper Timsah Formation consists of ferruginous sandstones, oolitic ironstone, and mudstone. Fluvial sandstone forms the Umm Brammily Formation. The oolitic sandy ironstone (2–2.5 m thick) is rich in dark red oolitic hematite and goethite. The ironstone deposit ranges in composition from oolitic sandy ironstone to oolitic ironstone. The distribution of iron minerals is extremely consistent with the iron concentration grade indicated by the Landsat-8 and ASTER Brand Ratios. Five main fault sets to control the extension of the ironstone beds: NNE-SSW left-lateral strike-slip faults (set 1); ENE-WSW normal faults (set 2); NNW-SSE normal faults (set 3); NW–SE normal faults (set 4); and NE-SW normal faults (set 5). The subsequent displacement of Set 3 faults increased the depth of the ironstone bed, which raised the sedimentary overburden load and increased the cost of ironstone exploitation, as well as the absence of iron ore exploitation zones bordering the Nile River.

Accelerated photonic design of coolhouse film for photosynthesis via machine learning

PGC-1α activation to enhance macrophage immune function in mycobacterial infections

Nontuberculous Mycobacteria (NTM) are a heterogeneous group of environmental microorganisms with distinct human pathogenesis. Their incidence and prevalence are rising worldwide, due in part to elevated antimicrobial resistance which complicates treatment and potential successful outcomes. Although information exists on the clinical significance of NTMs, little is known about host immune response to infection. NTM infections alter macrophage mitochondrial capacity and decrease ATP production, efficient immune response, and bacterial clearance. Transcription factor peroxisome proliferator activated receptor (PPAR) γ coactivator-1α (PGC-1α) is a master regulator of mitochondrial biogenesis, influencing metabolism, mitochondrial pathways, and antioxidant response. Mitochondrial transcription factor A (TFAM) is a protein essential for mitochondrial DNA (mtDNA) genome stability, integrity, and metabolism. Both PGC-1α and TFAM regulate mitochondrial biogenesis and activity, and their disruption is linked to inflammatory signaling and altered macrophage function. We show that NTM causes macrophage mitochondrial damage and disrupted bioenergetics. Mechanistically we show that this is related to attenuation of expression of PGC-1α and TFAM in infected macrophages. Importantly, rescuing expression of PGC-1α and TFAM using pharmacologic approaches restored macrophage immune function. Our results suggest that pharmacologic approaches to enhance mitochondrial function provide a novel approach to target macrophage immune function and means to combat NTM infections.

Hypothyroid Myopathy with Muscle Pseudohypertrophy

Sorghum yield prediction based on remote sensing and machine learning in conflict affected South Sudan

The hypolipidemic effect of MI-883, the combined CAR agonist/ PXR antagonist, in diet-induced hypercholesterolemia model

Abstract Constitutive androstane receptor (CAR) and pregnane X receptor (PXR) are closely related nuclear receptors with overlapping regulatory functions in xenobiotic clearance but distinct roles in endobiotic metabolism. Car activation has been demonstrated to ameliorate hypercholesterolemia by regulating cholesterol metabolism and bile acid elimination, whereas PXR activation is associated with hypercholesterolemia and liver steatosis. Here we show a human CAR agonist/PXR antagonist, MI-883, which effectively regulates genes related to xenobiotic metabolism and cholesterol/bile acid homeostasis by leveraging CAR and PXR interactions in gene regulation. Through comprehensive analyses utilizing lipidomics, bile acid metabolomics, and transcriptomics in humanized PXR-CAR-CYP3A4/3A7 mice fed high-fat and high-cholesterol diets, we demonstrate that MI-883 significantly reduces plasma cholesterol levels and enhances fecal bile acid excretion. This work paves the way for the development of ligands targeting multiple xenobiotic nuclear receptors. Such ligands hold the potential for precise modulation of liver metabolism, offering new therapeutic strategies for metabolic disorders.

Cuproptosis-related lncRNAs and genes: Potential markers for glioblastoma prognosis and treatment

Despite the availability of various treatment options, glioblastoma (GBM) remains an extremely aggressive form of glioma with a poor prognosis. In recent studies, regulatory cell death (RCD) has been identified as an effective mechanism to suppress glioma. Cuproptosis, caused by intracellular copper, is a novel RCD process that affects chemotherapy efficacy and glioma progression; however, the precise function of cuproptosis-related lncRNAs (CRLs) and cuproptosis-related genes (CRGs) in GBM remains uncertain. To determine whether CRLs and CRGs have prognostic significance, a GBM cohort in TCGA to build a novel cuproptosis-related risk model. Two high-risk CRLs (AC091182.2, AC005229.4) and their co-expression CRGs (LIPT2, GLS) were identified and verified to constitute an independent prognostic indicator of GBM. RT-qPCR analysis confirmed that the high-risk CRLs and CRGs were highly expressed in GBM cells compared to normal astrocytes. By constructing a mouse GBM model, high-risk CRLs and CRGs were found to be expressed at higher levels in tumor tissues. Furthermore, to verify whether these CRLs and CRGs are associated with GBM cuproptosis, cuproptosis cell models were constucted in GBM cell lines and astrocyte by using Elesclomol and CuCl2. It was found that the expression of high-risk CRLs and CRGs was decreased upon cuproptosis-induced in GBM cells. Interestingly, normal astrocytes were less sensitive than GBM cells to cuproptosis-inducing drugs, and the effects of the drugs on the expression of the CRLs and CRGs in normal astrocytes were opposite to that of in GBM cells. In conclusion, by constructing a novel cuproptosis-related risk model, two high-risk CRLs and CRGs were identified. Their specific pointing to GBM has been demonstrated through a variety of experiments. These CRLs and CRGs might serve as prognostic markers and indicators for GBM and provide theoretical support for future GBM treatment.

CD4+ T-Cell Lymphoma Harboring a Chimeric Antigen Receptor Integration in <i>TP53</i>

Psychometric validation and cultural adaptation of the Persian Galveston orientation and amnesia test and orientation-log for assessing traumatic brain injury

Using resistor network models to predict the transport properties of solid-state battery composites

Abstract Solid-state batteries use composites of solid ion conductors and active materials as electrode materials. The effective transport of charge carriers and heat thereby strongly determines the overall solid-state battery performance and safety. However, the phase space for optimization of the composition of solid electrolyte, active material, additive is too large to cover experimentally. In this work, a resistor network model is presented that successfully describes the transport phenomena in solid-state battery composites, when benchmarked against experimental data of the electronic, ionic, and thermal conductivity of LiNi 0.83 Co 0.11 Mn 0.06 O 2 -Li 6 PS 5 Cl positive electrode composites. To highlight the broadness of the approach, literature data are examined using the proposed model. As the model is easily accessible and expandable, without the need for high computing power, it offers valuable guidance for experimentalists helping to streamline the tedious process of performing a multitude of experiments to understand and optimize the effective transport of composite electrodes.

Prevalence of prolonged transitional neonatal hypoglycemia and associated factors in Ethiopia: A systematic review and meta-analysis

Introduction Most neonates experience transient hypoglycemia, which typically responds well to treatment and is associated with a favorable prognosis. However, hypoglycemia persisting beyond 48 hours, termed prolonged transitional Neonatal hypoglycemia (PTNHG), can result in abrupt neuronal injury and long-term neurodevelopmental impairments. Identifying its prevalence and associated risk factors is critical to inform clinical practices and improve neonatal outcomes. Methods A weighted inverse-variance random-effects model was employed for the analysis. Heterogeneity among the studies was assessed using a forest plot, I2 statistics, and Egger’s test. Data extraction was conducted from May 20 to May 27, 2023, for studies published since 2020. A random blood sugar (RBS) concentration of &lt;47 mg/dL measured 48–72 hours after birth was used to define PTNHG. Eight studies comprising a total of 3686 neonates were included in the analysis. Results The pooled prevalence of PTNHG was 19.71% (95% CI: 16.85–22.56) with substantial heterogeneity (I2 = 79.20%, P &lt; 0.001). Subgroup analysis revealed that PTNHG prevalence was similar for studies with sample sizes &gt;400 and ≤400, at 18% (95% CI: 15–22) and 21% (95% CI: 17–26), respectively. Similarly, prevalence estimates were comparable when using RBS thresholds of &lt;47 mg/dL (21%; 95% CI: 16–27) and &lt;40 mg/dL (18%; 95% CI: 15–22). Significant factors associated with PTNHG included preterm birth (AOR = 3.31; 95% CI: 2.57–4.04), hypothermia (AOR = 3.41; 95% CI: 2.19–4.62), being an infant of a diabetic mother (IDM) (AOR = 4.71; 95% CI: 2.15–7.26), delayed breastfeeding initiation beyond one hour (AOR = 3.26; 95% CI: 2.03–4.49), and pathological jaundice (AOR = 2.37; 95% CI: 1.91–2.84). Conclusions Nearly one-fifth of hospitalized neonates experienced PTNHG. Fortunately, most of the associated risk factors were modifiable. Prioritizing early breastfeeding initiation, particularly in cesarean section deliveries and IDM cases, and integrating PTNHG management into national NICU guidelines could significantly reduce the burden of neonatal hypoglycemia. Trial registration Prospero ID: CRD42023424953. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023424953.

<i>Plaques en Prairie Fauchée</i> Tongue Lesions in Secondary Syphilis

Non-lethal sonodynamic therapy mitigates hypertensive renal fibrosis through the PI3K/AKT/mTORC1-autophagy pathway

A quantitative spatial cell-cell colocalizations framework enabling comparisons between in vitro assembloids and pathological specimens

Calculating age-specific prevalence rates of female genital mutilation / cutting (FGM/C) for use as an input variable in extrapolation calculations and as predictors of future prevalence in countries of origin

This paper proposes a refined method for calculating age-specific prevalence rates of Female Genital Mutilation/Cutting (FGM/C) to enhance the accuracy of estimates calculated using Yoder and Van Baelen’s Extrapolation-of-FGM/C-Countries-Prevalence-Data method. Previous studies, particularly in the United States, have faced limitations, including the failure to disaggregate prevalence data by age and overlooking historical trends. To address these limitations, this study outlines a comprehensive seven-step approach. Using Ethiopia as a case study, prevalence rates were calculated and aligned with target migrant population data. This involved adjusting age cohorts, extrapolating prevalence to younger age groups, and considering historical trends. Results demonstrate significant differences compared to previous estimates, indicating overestimation of girls at risk of FGM/C in some studies. The proposed method offers a standardized approach applicable beyond the United States, potentially improving estimates globally. By providing nuanced prevalence data, this method contributes to better understanding the true prevalence of FGM/C in migrant populations. This same method can also be used to predict future trends in FGM/C and other practices.

Alternative Complement Pathway Inhibition with Iptacopan in IgA Nephropathy

Machine learning optimized design of THz piezoelectric perovskite-based biosensor for the detection of formalin in aqueous environments

Abstract This investigation presents the development and characterization of an advanced piezoelectric perovskite-based biosensing platform optimized for formalin detection in aqueous media through the implementation of Locally Weighted Linear Regression (LWLR) machine learning algorithms. The sensor architecture operates within the terahertz spectral region and incorporates an advanced nanomaterial composite system comprising black phosphorus, gold nanostructures, graphene, and barium titanate to maximize detection sensitivity and operational performance metrics. The engineered platform integrates a circular graphene metasurfaces configuration with a gold-based H-resonator assembly and concentrically arranged circular ring resonators. Computational simulations demonstrate vigorous sensing capabilities across three discrete frequency bands, achieving remarkable sensitivity parameters of 444 GHzRIU⁻¹, accompanied by a quality factor of 5.970 and detection accuracy of 7.576. The integration of LWLR-based optimization protocols substantially enhances prediction accuracy while reducing computational time by ≥ 85% as well as cutting down the required resources. The proposed sensor architecture presents significant potential for environmental monitoring and clinical applications, offering a highly sensitive and efficient methodology for quantitative formalin detection in aqueous environments.

Flexible electro-hydraulic power chips

Comparisons of performances of structural variants detection algorithms in solitary or combination strategy

Structural variants (SVs) have been associated with changes in gene expression, which may contribute to alterations in phenotypes and disease development. However, the precise identification and characterization of SVs remain challenging. While long-read sequencing offers superior accuracy for SV detection, short-read sequencing remains essential due to practical and cost considerations, as well as the need to analyze existing short-read datasets. Numerous algorithms for short-read SV detection exist, but none are universally optimal, each having limitations for specific SV sizes and types. In this study, we evaluated the efficacy of six advanced SV detection algorithms, including the commercial software DRAGEN, using the GIAB v0.6 Tier 1 benchmark and HGSVC2 cell lines. We employed both individual and combination strategies, with systematic assessments of recall, precision, and F1 scores. Our results demonstrate that the union combination approach enhanced detection capabilities, surpassing single algorithms in identifying deletions and insertions, and delivered comparable recall and F1 scores to the commercial software DRAGEN. Interestingly, expanding the number of algorithms from three to five in the combination did not enhance performance, highlighting the efficiency of a well-chosen ensemble over a larger algorithmic pool.