Scientific Reports最新文献

Growing evidences have suggested the airway microbiota may participate in lung cancer progression. However, little was known about the relationship between airway microbiota and lung cancer associated systemic inflammation. Here we aimed to explore the association between sputum microbiota and systemic inflammation in lung cancer. The microbiota of spontaneous sputum samples from 51 non-small cell lung cancer (NSCLC) patients and 6 patients with lung benign nodules were sequenced via 16 S rRNA sequencing. Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and C reactive protein (CRP) were used to represent systemic inflammation. Patients were divided into 2 groups based on level of inflammatory biomarkers respectively (CRP_low versus CRP_high; NLR_low versus NLR_high; PLR_low versus PLR_high). α-diversity was significantly decreased in CRP_high and NLR_high patients. β diversity analysis based on weighted unifrac distance indicated that microbial community structure differed significantly between patients with different inflammation status. Lefse identified genera Porphyromonas, Selenomonas, Moryella, Megasphaera, Corynebacterium were enriched in CRP_low group. Compared with NLR_high, genera Veillonella, Neisseria, Bulleidia, Moryella were enriched in NLR_low group. For patients with different PLR level, genera Veillonella, Prevotella, Moryella, Selenomonas were increased in PLR_ low patients. Function analysis identified propionate metabolism pathway was significantly enriched in CRP_low and PLR_low groups. Moreover, RDA analysis showed that compared with PLR, NLR and CRP had strongest association with microbial community. Airway microbial structure differed between lung cancer with different systemic inflammation status. Patients with relative high inflammation status were associated with alteration of specific airway genera and microbial metabolic function.

This study investigated plant growth-promoting (PGP) mechanisms in Priestia aryabhattai VMYP6 and Paenibacillus sp. VMY10, isolated from tomato roots. Their genomes were initially assessed in silico through various approaches, and these observations were then compared with results obtained in vitro and in vivo. Both possess genes associated with the production of siderophores, indole acetic acid (IAA) and cytokinins (CKs), all of which have been shown to promote plant growth. The two strains were able to produce these compounds in vitro. Although both genomes harbor genes for phosphorus solubilization, only VMY10 demonstrated this ability in vitro. Genes linked to flagellar assembly and chemotaxis were identified in the two cases. Both strains were able to colonize plant roots, even though VMYP6 lacked motility and no flagella were observed microscopically. In the greenhouse, tomato plants inoculated with the strains showed increased biomass, leaf area, and root length. These findings underscore the importance of integrating in vitro assays, genomic analyses, and plant trials to gain a comprehensive insight into the PGP mechanisms of rhizobacteria like VMYP6 and VMY10. Such insight may contribute to improving the selection of strains used as biofertilizers in tomato, a major crop worldwide.

To reduce greenhouse emissions and producing electricity with the smallest environmental impact, developing solar power technology is one of the most important milestones to achieve. Thus, to improve the efficiency of the concentrated solar power (CSP) plants, with lower environmental impact, is of great interest. This work reports the development of nanofluids, a colloidal suspension of nanomaterials in a fluid, based on an environment-friendly base fluid for improving the performance of the heat transfer process in CSP plants. The nanofluids contain Pt nanoparticles in a linear silicone-based heat transfer fluid, and their stability is guaranteed for several weeks. Their properties of interest, density, surface tension, viscosity, isobaric specific heat and thermal conductivity were characterized to determine the performance of the nanofluids in solar thermal technology. Improvements of about 6% and 24% in specific heat and thermal conductivity were found, without significant increases in viscosity. In addition, their effect on the performance of collectors and heat exchangers in CSP using these nanofluids was analysed, and an enhancement of about 40% is found. Specific heat enhancements are also discussed in view of the strength of the interactions between methyl siloxane groups and low Miller index surfaces of Pt, with data from density functional theory simulations.

Periodic sensory inputs entrain oscillatory brain activity, reflecting a neural mechanism that might be fundamental to temporal prediction and perception. Most environmental rhythms and patterns in human behavior, such as walking, dancing, and speech do not, however, display strict isochrony but are instead quasi-periodic. Research has shown that neural tracking of speech is driven by modulations of the amplitude envelope, especially via sharp acoustic edges, which serve as prominent temporal landmarks. In the same vein, research on rhythm processing in music supports the notion that perceptual timing precision varies systematically with the sharpness of acoustic onset edges, conceptualized in the beat bin hypothesis. Increased envelope sharpness induces increased precision in localizing a sound in time. Despite this tight relationship between envelope shape and temporal processing, it is currently unknown how the brain uses predictive information about envelope features to optimize temporal perception. With the current EEG study, we show that the predicted sharpness of the amplitude envelope is encoded by pre-target neural activity in the beta band (15-25 Hz), and has an impact on the temporal perception of target sounds. We used probabilistic sound cues in a timing judgment task to inform participants about the sharpness of the amplitude envelope of an upcoming target sound embedded in a beat sequence. The predictive information about the envelope shape modulated task performance and pre-target beta power. Interestingly, these conditional beta-power modulations correlated positively with behavioral performance in the timing judgment task and with perceptual temporal precision in a click-alignment task. This study provides new insight into the neural processes underlying prediction of the sharpness of the amplitude envelope during beat perception, which modulate the temporal perception of sounds. This finding could reflect a process that is involved in temporal prediction, exerting top-down control on neural entrainment via the prediction of acoustic edges in the auditory stream.

Salivary cytokines have the potential to serve as biomarkers for evaluating cancer progression and treatment response in specific cancer types. This study explored salivary cytokine profiles in pediatric cancer patients and healthy controls, examining changes during chemotherapy. We conducted a prospective study involving newly diagnosed cancer patients and healthy controls under 19 years old. Saliva samples were collected at diagnosis, and three and six months post-diagnosis for cancer patients, while healthy controls provided samples at a single time point. Cytokine levels were analyzed using Luminex technology. Our study included 19 cancer patients (10 with leukemia, 5 with lymphoma, and 4 with solid tumors) and 128 healthy controls aged 4 to 18 years. At diagnosis, patients with leukemia and solid tumors showed elevated levels of interferon-γ, interleukin (IL)-1α, IL-1β, IL-4, IL-5, IL-8, IL-10, and tumor necrosis factor. After three months, IL-6, IL-10, and inducible protein-10 levels significantly increased, while IL-1α, IL-1β, and IL-8 rose by six months. These findings indicate that salivary cytokines are elevated at diagnosis and during initial treatment phases in pediatric cancer patients, highlighting saliva's potential as a noninvasive medium for early detection of systemic diseases in children.

Nocturnal polyuria is a major cause of nocturia, which affects quality of life. Aging-related decreases in nitric oxide production have been reported to contribute to salt-induced nocturnal polyuria. We posited that enhanced nitric oxide production from exercise could mitigate salt-induced nocturnal polyuria. To validate, we assessed the impact of 4 weeks of moderate-intensity exercise on intrarenal renin-angiotensin system activity and salt-induced polyuria during inactive periods in 80-week-old mice. The moderate-intensity exercise group (Mod-Ex) had increased nitric oxide production and suppressed intrarenal renin-angiotensin system compared to the sedentary group (Sed) (renal angiotensinogen level: Sed vs. Mod-Ex, 1.101 ± 0.077 vs. 0.630 ± 0.048 arbitrary unit, P = 0.002). This exercise also alleviated salt-induced polyuria during inactive periods (diurnal polyuria index: Sed vs. Mod-Ex, 0.292 ± 0.027 vs. 0.193 ± 0.023, P = 0.018). These effects were neutralized by suppression of nitric oxide production by oral administration of N^ω-Nitro-L-arginine methyl ester hydrochloride, an nitric oxide synthesis inhibitor. These findings indicate that exercise-induced improvements in salt-induced polyuria during inactive periods are caused by increases in nitric oxide production. In summary, increasing nitric oxide production may serve as a treatment method for salt-induced nocturnal polyuria in older adults.

This paper details the hardware implementation of a Universal Converter controlled by an Artificial Neural Network (ANN), utilizing key components such as six Insulated Gate Bipolar Transistors (IGBTs), two inductors, and two capacitors for energy storage and voltage smoothing. A Digital Signal Processor (DSP) serves as the core controller, processing real-time input and feedback signals, including voltage and current measurements, to dynamically manage five operational modes: rectifier buck, inverter boost, DC-DC buck, DC-DC boost, and AC voltage control. The pre-trained ANN algorithm generates pulse-width modulation (PWM) signals to control the switching of the IGBTs, optimizing timing and duty cycles for efficient operation. The system effectively accommodates both AC and DC inputs, ensuring stable outputs with minimal ripple by dynamically selecting the appropriate mode based on load requirements. Experimental results demonstrated that the ANN controller maintained total harmonic distortion (THD) below 5% in rectifier and inverter modes while achieving an overall efficiency of 94-96% in DC-DC modes. The controller's capability to adapt to real-time feedback significantly improved power conversion quality and reduced switching losses. This study confirms the efficacy of the ANN-controlled Universal Converter in meeting the demands of modern power systems through versatile and adaptive control.

This paper presents an in-pixel contrast enhancement circuit that performs image processing directly within the pixel circuit. The circuit leverages HyperFET, a hybrid device combining a MOSFET and a phase transition material (PTM), to enhance performance. It can be tuned for different modes of operation. In foreground enhancement mode, it suppresses low-intensity background pixels to nearly zero, isolating the foreground for better object visibility. In contrast enhancement mode, it improves overall image contrast. The contrast enhancement function is customizable both during the design phase and in real-time, allowing the circuit to adapt to specific applications and varying lighting conditions. A model of the designed pixel circuit is developed and applied to a full pixel array, demonstrating significant improvements in image quality. Simulations performed in HSPICE show a nearly 6x increase in Michelson Contrast Ratio (CR) in the foreground enhancement mode. Furthermore, process variation and Signal-to-Noise Ratio (SNR) analysis has been conducted to evaluate the robustness of the design under manufacturing variations. The simulation results indicate its potential for real-time, adaptive contrast enhancement across various imaging environments.

The main objective of this work is to study the mathematical model that combines stem cell therapy and chemotherapy for cancer cells. We study the model using the fractal fractional derivative with the Mittag-Leffler kernel. In the analytical part, we study the existence of the solution and its uniqueness, which was studied based on the fixed point theory. The equilibrium points were also studied and discussed after stem cell therapy, and the approximate solutions for the given model were obtained using the Adam Bashford method, which depends on interpolation with Lagrange polynomials. Finally, the model was simulated using the Mathematica software, and through the figures, we found that the components of the model approach the equilibrium point, which indicates the stability of the model at the equilibrium point. Also, the result of the numerical simulation and graphic for the concentration of cells over time indicate the effects of the therapies on the decay rate of tumor cells and the growth rate of effector cells to modify the cancer patient's immune system. It is worth noting that we simulated all the model components with different fractional orders, confirming the effect of stem cell therapy and chemotherapy on the cells and the decay of cancer cells.