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Executive impairment in schizophrenia is common, but the mechanism remains unclear. This is the first study to use simultaneously functional near-infrared spectroscopy (fNIRS) to monitor the hemodynamic response in schizophrenia during the MATRICS Consensus Cognitive Battery (MCCB). Here, we monitored relative changes in oxyhemoglobin concentration in the medial prefrontal cortex (mPFC) during Trail Making Test, Symbol Coding Test and Mazes Test of the MCCB in 63 patients (29 females) with schizophrenia and 32 healthy controls (15 females). Results showed that patients with schizophrenia scored lower than healthy controls on all three tests (P < 0.001), but mPFC activation was significantly higher during the test (P < 0.03). Higher activation of the mPFC may reflect abnormal information processing in schizophrenia. In addition, the results also showed sex differences in hemodynamic activation during the task in patients with schizophrenia, and fNIRS has the potential to be a clinical adjunct to screening for cognitive function in schizophrenia., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Raman spectroscopy is a kind of vibrational method that can rapidly and non-invasively gives chemical structural information with the Raman spectrometer. Despite its technical advantages, in practical application scenarios, Raman spectroscopy often suffers from interference, such as noises and baseline drifts, resulting in the inability to acquire high-quality Raman spectroscopy signals, which brings challenges to subsequent spectral analysis. The commonly applied spectral preprocessing methods, such as Savitzky-Golay smooth and wavelet transform, can only perform corresponding single-item processing and require manual intervention to carry out a series of tedious trial parameters. Especially, each scheme can only be used for a specific data set. In recent years, the development of deep neural networks has provided new solutions for intelligent preprocessing of spectral data. In this paper, we first creatively started from the basic mechanism of spectral signal generation and constructed a mathematical model of the Raman spectral signal. By counting the noise parameters of the real system, we generated a simulation dataset close to the output of the real system, which alleviated the dependence on data during deep learning training. Due to the powerful nonlinear fitting ability of the neural network, fully connected network model is constructed to complete the baseline estimation task simply and quickly. Then building the Unet model can effectively achieve spectral denoising, and combining it with baseline estimation can realize intelligent joint processing. Through the simulation dataset experiment, it is proved that compared with the classic method, the method proposed in this paper has obvious advantages, which can effectively improve the signal quality and further ensure the accuracy of the peak intensity. At the same time, when the proposed method is applied to the actual system, it also achieves excellent performance compared with the common method, which indirectly indicates the effectiveness of the Raman signal simulation model. The research presented in this paper offers a variety of efficient pipelines for the intelligent processing of Raman spectroscopy, which can adapt to the requirements of different tasks while providing a new idea for enhancing the quality of Raman spectroscopy signals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Cadmium (Cd) contamination in rice fields has been recognized as a severe global agro-environmental issue. To reach the goal of controlling Cd risk, we must pay more attention and obtain an in-depth understanding of the environmental behavior, uptake and translocation of Cd in soil-rice systems. However, to date, these aspects still lack sufficient exploration and summary. Here, we critically reviewed (i) the processes and transfer proteins of Cd uptake/transport in the soil-rice system, (ii) a series of soil and other environmental factors affecting the bioavailability of Cd in paddies, and (iii) the latest advances in regard to remediation strategies while producing rice. We propose that the correlation between the bioavailability of Cd and environmental factors must be further explored to develop low Cd accumulation and efficient remediation strategies in the future. Second, the mechanism of Cd uptake in rice mediated by elevated CO 2 also needs to be given more attention. Meanwhile, more scientific planting methods (direct seeding and intercropping) and suitable rice with low Cd accumulation are important measures to ensure the safety of rice consumption. In addition, the relevant Cd efflux transporters in rice have yet to be revealed, which will promote molecular breeding techniques to address the current Cd-contaminated soil-rice system. The potential for efficient, durable, and low-cost soil remediation technologies and foliar amendments to limit Cd uptake by rice needs to be examined in the future. Conventional breeding procedures combined with molecular marker techniques for screening rice varieties with low Cd accumulation could be a more practical approach to select for desirable agronomic traits with low risk., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Cadmium (Cd) is considered the primary dietary toxic element. Previous studies have demonstrated significant differences in heavy metal accumulation among crop species. However, this information in karst areas with low heavy metal activity is missing. In this study, the uptake and accumulation characteristics of cadmium in soil-crop samples of group 504 in the core karst region of East Asia were analyzed. Cadmium low-accumulating maize and rice were screened using cluster and Pareto analytic methods. In addition, a new method, the species-sensitive distribution model (SSD), was proposed, which could be used to estimate the environmental threshold for cadmium in regional cropland. The results showed that both maize and rice soils in the research area were contaminated with varying degrees of cadmium. The total concentrations of cadmium ω(T-Cd) in maize and rice fields are 0.18-1.32 and 0.20-4.42 mg kg -1 , respectively. The ω(T-Cd) of heavy metals in maize kernels and rice grains is 0.002-0.429 and 0.003-0.393 mg kg -1 , respectively. The bioaccumulation factor (BCF) of cadmium in maize ranged from 0.0079 to 0.9701, with a coefficient of variation of 1.71; the BCF of cadmium in rice ranged from 0.0074 to 0.1345, with a coefficient of variation of 0.99. According to cluster and Pareto analyses, the maize crop varieties with low cadmium accumulation suitable for local cultivation were screened as JHY809, JDY808, AD778, SN3H and SY13, and the rice varieties were DMY6188, GY725, NY6368, SY451 and DX4103. In addition, the environmental cadmium threshold ranges of 0.30-10.05 mg kg -1 and 0.89-24.39 mg kg -1 for maize and rice soils, respectively, were deduced in this study. This threshold will ensure that 5-95% of maize and rice will not be contaminated with cadmium in the soil., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)