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Since different quantities of white blood cells (WBCs) in solution possess an adaptive osmotic pressure of cells, the WBCs themselves and in solution have similar concentrations, resulting in them having similar dielectric properties. Therefore, a microwave sensor could have difficulty in sensing the quantity variation when WBCs are in solution. This paper presents a highly sensitive, linear permittivity-inspired microwave biosensor for WBCs, counting through the evaporation method. Such a measurement method is proposed to record measurements after the cell solution is dripped onto the chip and is completely evaporated naturally. The proposed biosensor consists of an air-bridged asymmetric differential inductor and a centrally located circular fork-finger capacitor fabricated on a GaAs substrate using integrated passive fabrication technology. It is optimized to feature a larger sensitive area and improved Q-factor, which increases the effective area of interaction between cells and the electromagnetic field and facilitates the detection of their changes in number. The sensing relies on the dielectric properties of the cells and the change in the dielectric constant for different concentrations, and the change in resonance properties, which mainly represents the frequency shift, corresponds to the macroscopic change in the concentration of the cells. The microwave biosensors are used to measure biological samples with concentrations ranging from 0.25 × 106 to 8 × 106 cells per mL in a temperature (26.00 ± 0.40 °C) and humidity (54.40 ± 3.90 RH%) environment. The measurement results show a high sensitivity of 25.06 Hz/cells·mL−1 with a highly linear response of r2 = 0.99748. In addition, a mathematical modeling of individual cells in suspension is performed to estimate the dielectric constant of individual cells and further explain the working mechanism of the proposed microwave biosensor. [ABSTRACT FROM AUTHOR]

The selection of shade-tolerant and high-light-efficient soybean varieties is one of the important research elements of the maize-soybean ribbon complex cropping model. By analyzing the differences in leaf morphology and photosynthetic physiological responses between wild and cultivated soybean seedlings under normal and shaded conditions, we can reveal their shade-tolerance mechanisms and response differences, which can provide a theoretical basis for the breeding of new shade-tolerant and high-light-efficient soybean varieties. In this study, two types of cultivated soybean (Nandou 12 and Tianlong No.1) and two types of wild soybean (W1 and W2) were used as experimental materials to investigate their response to shade under two light environments: natural light and 50% shade. The results showed that the specific leaf weight, leaf thickness, fenestrated tissue thickness, net photo-synthetic rate, stomatal conductance, and photosynthetic pigment content of wild and cultivated soybean were significantly lower under shade stress than under natural light. In shade, cultivated soybean showed higher variation in net photosynthetic rate, photosynthetic pigment content, spongy tissue thickness, and leaf area than wild soybean, while specific leaf weight and ratio of fenestrated tissue to spongy tissue were significantly lower than wild soybean. Wild soybean can improve its adaptation to low light conditions by maintaining Chlb content, increasing the proportion of chlorophyll in photosynthetic pigments and stimulating potential maximum photosynthetic activity as a response. The differences in the response of wild and cultivated soybean to shade conditions could provide theoretical support for future breeding of shade-tolerant soybean. [ABSTRACT FROM AUTHOR]

Background: The early detection of clinically significant prostate cancer (csPCa) through the integration of multidimensional parameters presents a promising avenue for improving survival outcomes for this fatal disease. This study aimed to assess the contribution of prostate transition zone (TZ) to predictive models based on the prostate health index (PHI), with the goal of enhancing early detection of csPCa in the prostate-specific antigen (PSA) gray zone. Methods: In this observational cross-sectional study, a total of 177 PSA gray zone patients (total prostate-specific antigen [tPSA] level ranging from 4.0 to 10.0 ng/mL) were recruited and received PHI detections from August 2020 to March 2022. Prostatic morphologies especially the TZ morphological parameters were measured by transrectal ultrasound (TRUS). Results: Univariable logistic regression indicated prostatic morphological parameters including total prostate volume (PV) indexes and transitional zone volume indexes were all associated with csPCa (P <.05), while the multivariable analysis demonstrated that C-reactive protein (CRP), PHI, PHI density (PHID), and PHI transition zone density (PHI-TZD) were the 4 independent risk factors. The receiver-operating characteristic (ROC) curve analysis suggested that integrated predictive models (PHID, PHI-TZD) yield area under the curves (AUCs) of 0.9135 and 0.9105 in csPCa prediction, which shows a relatively satisfactory predictive capability compared with other predictors. Moreover, the PHI-TZD outperformed PHID by avoiding 30 patients' unnecessary biopsies while maintaining 74.36% specificity at a sensitivity of 90%. Decision-curve analysis (DCA) confirmed the comparable performance of the multivariable full-risk prediction models, without the inclusion of the net benefit, thereby highlighting the superior diagnostic efficacy of PHID and PHI-TZD in comparison with other diagnostic models, in both univariable and multivariable models. Conclusion: Our data confirmed the value of prostate TZ morphological parameters and suggested a significant advantage for the TZ-adjusted PHI predictive model (PHI-TZD) compared with PHI and PHID in the early detection of gray zone csPCa under specific conditions. [ABSTRACT FROM AUTHOR]