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Chlorination-controlled aggregation and film-formation kinetics enabling high-efficiency organic solar cells with low-cost linear conjugated polymers
Enhancing fruit supply chain traceability through blockchain and cryptographic protocols for achieving UN sustainable development goals
Environmental and economic benefits of UHPFRC intervention in bridge management for the Swiss network
Combination of quantum-based optimizer and feature pyramid network for intrusion detection in Cloud-IoT environments
Author Correction: Directed rescue strategy for enhanced implant osteointegration in aged rats
Differences in motor skill-related physical fitness between moderately thin and normal weight rural Ethiopian children (ages 5–7)
A primary auditory cortex-anterior cingulate cortex circuit underlying cross-modal visceral pain modulation
Selective Lis1 inactivation disrupts migration and positioning of cortical somatostatin interneurons
Author Correction: High-order harmonic generation in an organic molecular crystal
Challenges in strengthening sentinel surveillance network during COVID-19 pandemic in Africa
Record-breaking emergence of upstream-downstream zonal-consistent variation in the Eurasian jet axis
Abstract Eurasian weather/climate extremes are often considerably linked to the meandering and/or latitudinal shifts of upper-level westerly jet, but the variation and impact of the upstream-downstream zonal consistency (UDZC) in the Eurasian jet axis are less known. Here we report a record-breaking emergence of an enhanced UDZC during the past two-to-three decades. In particular, the upstream-downstream covariance has increased from <10% to >60%, with the Eurasian upper-tropospheric westerly wind anomalies dominated by the Eurasian jet intensity change mode, which prompts a large-scale interplay between Asian and Pacific subtropical highs and thereby induces mega-shifts in the distribution patterns of circulation and climate anomalies across Eurasia. Such large-range circulation adjustments are also accompanied by a circumglobal Silk Road teleconnection, a Rossby wavetrain with zonal wavenumber 6, which originates from the Northeast Atlantic and connects Asian climate with western Europe and North America heatwave and drought conditions. Climate model simulations suggest that the UDZC would further intensify as the northern mid-latitude warming becomes more pronounced. Our results highlight that the emergence of enhancing UDZC in the Eurasian jet axis is capable of triggering planetary-scale climate extremes even across the whole Northern Hemisphere, imposing more serious climate threats.
Patients with tuberculosis and diabetes show altered clinical and biochemical parameters during anti-TB treatment
Abstract Type-2 diabetes mellitus (DM) increases tuberculosis (TB) risk and can worsen treatment outcomes. Both diseases and their treatments induce significant metabolic and biochemical perturbations that influence disease progression and management. This study longitudinally evaluated clinical, metabolic, and serum biochemical changes in patients with pulmonary TB with and without DM before and during anti-TB therapy. Ninety-five adult patients newly diagnosed with pulmonary TB in Ghana were stratified into TB-Only ( n = 49; HbA1c < 6.5%) and TB-DM ( n = 46; HbA1c ≥ 6.5%) groups, including treated (TB-DMt) and untreated (TB-DMnt) diabetes subgroups. Serum samples collected at baseline (t 0 ), day 28 (t 28 ), and day 56 (t 56 ) were analyzed for electrolytes, renal function, liver enzymes, and lipid profiles using validated clinical chemistry analyzer. TB-DM cohorts exhibited significantly lower chloride levels at all time points relative to the TB-Only cohort (e.g., 98 vs. 100 mmol/L at t 0 , p < 0.001). Hyponatremia (serum sodium < 136 mmol/L) was prevalent during the intensive anti-TB treatment phase, affecting 53.1% of TB-Only patients, 61.1% of TB-DMt patients, and 70.0% of TB-DMnt patients. Liver function tests revealed elevated bilirubin, gamma-glutamyl transferase (g-GT), alkaline phosphatase (ALP), and alanine aminotransferase (ALT) levels, particularly in TB-DMnt patients, with normalization over time. Lipid profiles showed a pro-atherogenic pattern with elevated triglycerides and total cholesterol ( p < 0.05). High-density and low-density lipoproteins were increased at select time points. Positive correlations were noted among albumin, cholesterol fractions, and electrolytes. Primary microbiological treatment outcomes, including sputum conversion and completion rates, were similar regardless of diabetic status. The distinctive metabolic and biochemical derangements in TB-DM, especially untreated diabetes, highlight the importance of integrated clinical management. Elevated hepatic enzymes in TB-DMnt may delay metformin initiation, suggesting a need to optimize timing post hepatic recovery, while the prevalence of hyponatremia underscores the need for routine electrolyte monitoring in TB patients with diabetes. The dysregulated lipid profile highlights cardiovascular risk that warrants routine monitoring. Despite metabolic challenges, effective TB treatment outcomes are achievable with comprehensive care.
Electrochemically Tuned Crystal Tectonics in Crack-Resistant Textured Oxide Cathode Films for Electrochemical Energy Storage
Advances and challenges in non-canonical nucleic acids data storage
Gaussian process regression with physics-guided pseudo-sample augmentation for wear prediction under sparse measurements in milling
Metabolic engineering of doxorubicin biosynthesis through P450-redox partner optimization and structural analysis of DoxA
Abstract Doxorubicin, a widely used chemotherapy drug, is produced by Streptomyces peucetius ATCC27952. The biosynthesis relies on the cytochrome P450 monooxygenase DoxA, which catalyzes three consecutive late-stage oxidation steps. However, conversion from daunorubicin to doxorubicin is inefficient, necessitating semi-synthetic industrial manufacturing. Here, we address key limitations in DoxA catalysis. We identify the natural redox partners ferredoxin Fdx4 and ferredoxin reductase FdR3 by transcriptomic analysis. We discovered the vicinal oxygen chelate family protein DnrV to prevent product inhibition by binding doxorubicin. Structural analysis of DoxA and density functional theory (DFT) calculations reveal that inefficient C14 hydroxylation results from the unfavorable anti-conformation of the methyl ketone side chain of daunorubicin. We harness these advances for rational strain engineering, leading to an 180% increase in doxorubicin yields and an improved production profile. This study provides singular insights into enzymatic constraints in anthracycline biosynthesis and facilitates cost-effective manufacturing to meet the growing global demand for doxorubicin.
Glucose-to-albumin ratio predicts short-term mortality in critically ill patients with acute pancreatitis
Binding properties of sulfur to enable solvent-free fabrication of high-performance polymer-free sulfur-carbon positive electrodes
Abstract The development of a scalable, cost-effective and environmentally benign manufacturing of binder-free sulfur positive electrodes can make substantial advance for lithium-sulfur (Li | |S) batteries as sustainable competitors to lithium-ion systems. Here we show a solvent- and binder-free method to fabricate sulfur-carbon composite electrodes directly on aluminum foil via thermal-assisted dry pressing. A key finding is the role of sulfur as a structural binder, where its softening, distribution, and adhesion properties enable the formation of mechanically robust electrodes without polymer binders. Systematic experimental characterizations and computational modeling reveal the underlying mechanisms governing electrodes formation and electrochemical performance. The developed binder-free positive electrodes achieve a reversible capacity of 932 mAh g⁻¹ after 500 cycles at 1.0 C rate; for comparison, conventional slurry-cast positive electrodes containing 10 wt.% binder deliver lower capacity under the same electrochemical test conditions. This scalable process has the potential to reduce fabrication costs by a factor of 2.1 while eliminating hazardous solvents and binders, offering a sustainable and cost-effective approach to advancing Li | |S battery technology.
Multi-scale entropy analysis of acoustic emission for gearbox fault severity classification
Abstract Acoustic emission (AE) sensors offer significant potential for early fault detection in rotating machinery through the monitoring of high-frequency transients. However, extracting effective features from complex AE signals remains challenging for automated fault severity classification across multiple damage mechanisms. This study investigates multi-scale entropy methods for extracting a computationally efficient set of 16 non-linear information entropy features from AE signals to diagnose gearbox fault severity. Three approaches were systematically compared: Composite Multi-Scale Entropy (CMSE), Hierarchical Multi-Scale Entropy (HMSE), and Composite Hierarchical Multi-Scale Entropy (CHMSE). Experimental data were collected from a spur gearbox test rig operating under controlled conditions, with artificially induced faults representing four damage mechanisms (pitting, broken teeth, root cracks, and scuffing) at nine severity levels each, providing the most granular assessment reported in the entropy-based fault diagnosis literature. Features extracted using each multi-scale method were classified using several classical machine learning models. The CHMSE combined with Random Forests (RF) models achieved the highest classification accuracy (97.37-99.50%), representing a 1-4% improvement over conventional single-scale methods and demonstrating superior performance compared to statistical features and alternative machine learning models. SHAP-based interpretability analysis revealed that generalized entropy measures, specifically Rényi entropy and Tsallis entropy, emerge as primary discriminators across CMSE, HMSE, and CHMSE approaches, with threshold entropy and log energy entropy demonstrating substantial discriminative power when combined with hierarchical decomposition methods (HMSE and CHMSE). Statistical analysis confirmed significant performance improvements (p <0.05) for the hierarchical approaches. These findings demonstrate that CHMSE-based feature extraction enables reliable AE-based condition-monitoring systems for predictive maintenance in industrial gearboxes.