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Objective To investigate the enhancing effect of platycodon grandiflorum saponin D on the sensitivity of human rectal cancer drug-resistant cell line SW1463 to oxaliplatin (Oxa). Methods Human rectal cancer cell line SW1463 was collected to establish a stable oxaliplatin-resistant cell strain SW1463/Oxa. The constructed cell strain SW1463/Oxa was randomly divided into platycodon grandiflorum saponin D group, Oxa group, platycodon saponin D+Oxa group and control group. The cell proliferation curve was detected by MTT. Deoxyribonucleic acid methyltransferase 3a (DNMT3a), phosphorylated histone γ-H2AX, DNA double strand repair protein RAD51 and signal transducer and activator of transcription 3(STAT3) messenger RNA (mRNA) expression were detected by RT-qPCR. DNMT3a, γ-H2AX, RAD51, STAT3 protein expression and phosphorylated STAT3(p-STAT3) level were detected by Western blot. Results Human rectal cancer drug resistant cell strain SW1463/Oxa was successfully constructed. Compared with the control group and Oxa group, the cell proliferation, DNMT3a, RAD51, STAT3 mRNA and protein expression and p-STAT3 level of platycodon saponin D group and platycodon saponin D+Oxa group decreased(P＜0.05), and the expression of γ-H2AX mRNA and protein increased(P＜0.05). Conclusions Platycodon grandiflorum saponin D may enhance the chemo-sensitivity of human rectal cancer drug-resistant cell strain SW1463/Oxa to Oxa, and the potential mechanism is inhibition of expression of DNMT3a, RAD51, STAT3 and promotion of expression of γ-H2AX.

Apple is an important cash crop in China, and the prediction of its freshness can effectively reduce its storage risk and avoid economic loss. The change in the concentration of odor information such as ethylene, carbon dioxide, and ethanol emitted during apple storage is an important feature to characterize the freshness of apples. In order to accurately predict the freshness level of apples, an electronic nose system based on a gas sensor array and wireless transmission module is designed, and a neural network prediction model using an improved Sparrow Search Algorithm (SSA) based on chaotic sequence (Tent) to optimize Back Propagation (BP) is proposed. The odor information emitted by apples is studied to complete an apple freshness prediction. Furthermore, by fitting the relationship between the prediction coefficient and the input vector, the accuracy benchmark of the prediction model is set, which further improves the prediction accuracy of apple odor information. Compared with the traditional prediction method, the system has the characteristics of simple operation, low cost, reliable results, mobile portability, and it avoids the damage to apples in the process of freshness prediction to realize non-destructive testing. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to explore the clinical value of the static amplitude of low-frequency fluctuation (sALFF) and dynamic amplitude of low-frequency fluctuation (dALFF) in the identification of brain functional alterations in degenerative cervical myelopathy (DCM) patients. Methods: Voxel-wise sALFF and dALFF of 47 DCM patients and 44 healthy controls were calculated using resting-state fMRI data, and an intergroup comparison was performed. The mean of sALFF or dALFF data were extracted within the resultant clusters and the correlation analysis of these data with the clinical measures was performed. Furthermore, whole-brain-wise and region-wise multivariate pattern analyses (MVPAs) were performed to classify DCM patients and healthy controls. sALFF and dALFF were used to predict the prognosis of DCM patients. Results: The findings showed that (1) DCM patients exhibited higher sALFF within the left thalamus and putamen compared with that of the healthy controls. DCM patients also exhibited lower dALFF within bilateral postcentral gyrus compared with the healthy controls; (2) No significant correlations were observed between brain alterations and clinical measures through univariate correlation analysis; (3) sALFF (91%) and dALFF (95%) exhibited high accuracy in classifying the DCM patients and healthy controls; (4) Region-wise MVPA further revealed brain regions in which functional patterns were associated with prognosis in DCM patients. These regions were mainly located at the frontal lobe and temporal lobe. Conclusion: In summary, sALFF and dALFF can be used to accurately reveal brain functional alterations in DCM patients. Furthermore, the multivariate approach is a more sensitive method in exploring neuropathology and establishing a prognostic biomarker for DCM compared with the conventional univariate method. [ABSTRACT FROM AUTHOR]

In the process of growth, apples' ripening, storage, transportation, and processing, the appearance and internal physiological characteristics will have some changes because of the effect of time and physical attributes. A series of problems, such as the false ripeness and putrefaction of fruit, will bring huge economic losses to fruit vendors and harm to consumers. In this paper, an odor recognition system has been designed for the fast evaluation of the freshness characteristics of apples, which is based on the freshness characteristics of Fuji apple. A series of apple-air mixture with equivalent model was established by studying the change of gas concentration during the growth and storage of apples. The continuous projection algorithm (Successive Projections Algorithm, SPA) is used to optimize the sensor array to solve the problems of collinearity and overlap and also to eliminate the abnormal and redundant sensors. ZigBee wireless sensor network is adopted to send data to host computer, and BP (Error Backpropagation) neural network algorithm optimized by SFLA (shuffled complex evolution, SCE + Particle Swarm Optimization, PSO) algorithm is used to recognize gas data, which greatly improves the training speed and precision of neural network. The experimental results show that the detection accuracy of the Fuji apples freshness is 98.67% and can quickly and comprehensively identify the freshness of apples. [ABSTRACT FROM AUTHOR]

Soil drought and nitrogen (N) deposition can influence the biogenic volatile organic compound (BVOC) emissions and thereby their ozone (O 3) and secondary organic aerosol (SOA) formation. This study addressed their single and combined effects on BVOC emissions of Pinus thunbergii by laboratory simulation experiments. The results showed that light drought (LD, 50% soil volumetric water content (VWC)) stimulated isoprene, monoterpene, sesquiterpene, and total BVOC emissions, while moderate drought (MD, 30% and 40% VWC) and severe drought (SD, 10% and 20% VWC) inhibited their emissions (except for sesquiterpene in 20% VWC). N deposition decreased other VOC emissions and increased isoprene and sesquiterpene emissions. Total BVOCs and monoterpene were stimulated in low N deposition (LN, 2 g N/(m2·yr)) and inhibited in moderate (MN, 5 g N/(m2·yr)) and high N deposition (HN, 10 g N/(m2·yr)). Under combined treatment of soil drought and N deposition, total BVOC, monoterpene, and other VOC emissions were inhibited, sesquiterpene had no significant change, and isoprene emission was inhibited in MD combined treatment but promoted in SD. The O 3 formation potential (OFP) and SOA formation potential (SOAP) from the changed BVOC emissions were calculated, OFP and SOAP of BVOC emissions and their compositions varied significantly among the treatments. Our study provided theoretical basis for assessing the impact of climate change and atmospheric pollution on BVOC emissions and their contribution to the formation of secondary atmospheric pollution. [Display omitted] • Monoterpene was the dominant BVOCs for P. thunbergii among all the treatments. • BVOC emission was promoted in light drought while suppressed in moderate and severe drought. • Total BVOC and monoterpene rose in low N deposition and reduced in moderate and high N deposition. • Combined treatment inhibited total BVOC, monoterpene, and other VOC emissions. • OFP and SOAP of BVOC emissions varied significantly among the treatments. [ABSTRACT FROM AUTHOR]

In this paper, we study the construction of confidence intervals for a nonparametric regression function under a negatively associated sample by using the blockwise technique. It is shown that the blockwise empirical likelihood (EL) ratio statistic is asymptotically χ2 distributed. The result is used to obtain EL-based confidence intervals for a nonparametric regression function. The results of a simulation study on the finite sample performance of the proposed confidence intervals are reported. [ABSTRACT FROM AUTHOR]

Accurate biogenic volatile organic compound (BVOC) emission estimations are essential for developing effective air pollution control measures. Chinese BVOC emissions were calculated at a spatial resolution of 36 km × 36 km for 2008–2018 using the Model of Emissions of Gases and Aerosols from Nature. A statistical method was developed to obtain more accurate emission rates based on large numbers of observations from China and other countries. The most detailed and accurate vegetation investigations at high resolutions were used to determine the distributions of leaf biomass and coverage for 82 vegetation species and types. The results show that the national BVOCs emissions in China in 2018 were large, 58.89 Tg, with isoprene, monoterpene, sesquiterpene, and other VOCs accounting for 63.60%, 11.35%, 2.18%, and 22.87% of the emissions, respectively. Broadleaf trees exhibited the largest isoprene and total BVOC emissions. The biogenic emissions and compositions displayed strong seasonal variations, and isoprene was significantly more sensitive to seasonality. The emissions were concentrated in the Greater Khingan Mountain, Changbai Mountain, Qinling Mountain, southeast and southwest forest areas, and Hainan Province because of their larger distributions of broadleaf trees with higher emission potentials. During 2008–2018, BVOC emissions increased by 20.18% at an annual rate of 2.03%, and isoprene exhibited the greatest enhancement of 32.67%, which was primarily due to the increase in leaf biomass. The regions with the largest growth were distributed in the Greater Khingan and Changbai Mountains, and the Sichuan, Hunan, and Hubei Provinces, which was primarily the result of the substantial increase in volumes of trees with higher emission rates. The uncertainty of our estimates was evaluated by comparing the applied basal emission factors, vegetation coverages, meteorological data, and emission algorithms from previous studies, and it was estimated to be approximately −36.5–4.6%. Unlabelled Image • BVOC emissions in China in 2018 were 58.89 Tg, with isoprene accounting for 63.60%. • Emissions were concentrated in northeast, southeast and southwest forest areas, and Hainan Province. • BVOC emissions increased by 20.18% during 2008–2018. [ABSTRACT FROM AUTHOR]

• Substrate combinations in CWs was a novel way for mitigating GWPs. • Substrate combinations significantly changed the microbial communities in CWs. • Despite the enhancement on N removal, walnut shell resulted in remarkable CH 4 flux. • The combination of walnut shell and Mn ore released the least N 2 O. Climate warming would be generally influenced by the quantity and component of greenhouse gases during the carbon and nitrogen removal in constructed wetlands (CWs). In this study, the impacts of the combinations by walnut shell (organic-rich substrate improving denitrification), manganese (Mn) ore (electron-exchange substrate transferring CH 4 to CO 2) and activated alumina (phosphorus-adsorption substrate) on global warming potentials (GWPs) were investigated to propose a strategy for both mitigating GWPs and performing well in wastewater treatment. During hybrid CWs, the highest COD and TP removal efficiencies were respectively 89.4% and 98.1% in CWs with the substrate combination of Mn ore and activated alumina, and the highest TN removal efficiency was in CWs with walnut shell and Mn ore. The substrate combination of walnut shell and Mn ore would simultaneously strengthen the nitrification and denitrification process resulting in the lowest N 2 O flux in CWs. The combinations of Mn ore with walnut shell or activated alumina could significantly decrease the GWPs through promoting the conversion of CH 4 to CO 2 due to the better redox potential environment favorable for methanotrophs (pmoA) instead of methanogenesis (mcrA) provided by Mn ore. This study provided a feasible way to mitigate climate warming during wastewater treatment in CWs by using substrate combination of Mn ore and walnut shell. [ABSTRACT FROM AUTHOR]

Soil drought and nitrogen (N) deposition can influence the biogenic volatile organic compound (BVOC) emissions and thereby their ozone (O 3 ) and secondary organic aerosol (SOA) formation. This study addressed their single and combined effects on BVOC emissions of Pinus thunbergii by laboratory simulation experiments. The results showed that light drought (LD, 50% soil volumetric water content (VWC)) stimulated isoprene, monoterpene, sesquiterpene, and total BVOC emissions, while moderate drought (MD, 30% and 40% VWC) and severe drought (SD, 10% and 20% VWC) inhibited their emissions (except for sesquiterpene in 20% VWC). N deposition decreased other VOC emissions and increased isoprene and sesquiterpene emissions. Total BVOCs and monoterpene were stimulated in low N deposition (LN, 2 g N/(m 2 ·yr)) and inhibited in moderate (MN, 5 g N/(m 2 ·yr)) and high N deposition (HN, 10 g N/(m 2 ·yr)). Under combined treatment of soil drought and N deposition, total BVOC, monoterpene, and other VOC emissions were inhibited, sesquiterpene had no significant change, and isoprene emission was inhibited in MD combined treatment but promoted in SD. The O 3 formation potential (OFP) and SOA formation potential (SOAP) from the changed BVOC emissions were calculated, OFP and SOAP of BVOC emissions and their compositions varied significantly among the treatments. Our study provided theoretical basis for assessing the impact of climate change and atmospheric pollution on BVOC emissions and their contribution to the formation of secondary atmospheric pollution., 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 Elsevier Ltd. All rights reserved.)

Purpose: Computer-aided diagnostic methods were used to compare the characteristics of the Original COVID-19 and its Delta Variant. Methods: This was a retrospective study. A deep learning segmentation model was applied to segment lungs and infections in CT. Three-dimensional (3D) reconstruction was used to create 3D models of the patient's lungs and infections. A stereoscopic segmentation method was proposed, which can subdivide the 3D lung into five lobes and 18 segments. An expert-based CT scoring system was improved and artificial intelligence was used to automatically score instead of visual score. Non-linear regression and quantitative analysis were used to analyze the dynamic changes in the percentages of infection (POI). Results: The POI in the five lung lobes of all patients were calculated and converted into CT scores. The CT scores of Original COVID-19 patients and Delta Variant patients since the onset of initial symptoms were fitted over time, respectively. The peak was found to occur on day 11 in Original COVID-19 patients and on day 15 in Delta Variant patients. The time course of lung changes in CT of Delta Variant patients was redetermined as early stage (0-3 days), progressive and peak stage (4-16 days), and absorption stage (17-42 days). The first RT-PCR negative time in Original COVID-19 patients appeared earlier than in Delta Variant patients (22 [17-30] vs. 39 [31-44], p < 0.001). Delta Variant patients had more re-detectable positive RT-PCR test results than Original COVID-19 patients after the first negative RT-PCR time (30.5% vs. 17.1%). In the early stage, CT scores in the right lower lobe were significantly different (Delta Variant vs. Original COVID-19, 0.8 ± 0.6 vs. 1.3 ± 0.6, p = 0.039). In the absorption stage, CT scores of the right middle lobes were significantly different (Delta Variant vs. Original COVID-19, 0.6 ± 0.7 vs. 0.3 ± 0.4, p = 0.012). The left and the right lower lobes contributed most to lung involvement at any given time. Conclusion: Compared with the Original COVID-19, the Delta Variant has a longer lung change duration, more re-detectable positive RT-PCR test results, different locations of pneumonia, and more lesions in the early stage, and the peak of infection occurred later., Competing Interests: Authors YH and YZ were employed by the company Heilongjiang Tuomeng Technology Co. Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bai, Lin, Wang, Cai, Huang, Su, Yao, Wen, Li, Huang, Zhao, Xia, Lei, Yang and Qiu.)

The activity of urate oxidase was lost during hominoid evolution, resulting in high susceptibility to hyperuricemia and gout in humans. In order to develop a more "human-like" uricase for therapeutic use, exon replacement/restoration and site-directed mutagenesis were performed to obtain porcine-human uricase with higher homology to deduced human uricase (dHU) and increased uricolytic activity. In an exon replacement study, substitution of exon 6 in wild porcine uricase (wPU) gene with corresponding exon in dhu totally abolished its activity. Substitutions of exon 5, 3, and 1-2 led to 85%, 60%, and 45% loss of activity, respectively. However, replacement of exon 4 and 7-8 did not significantly change the enzyme activity. When exon 5, 6, and 3 in dhu were replaced by their counterparts in wpu, the resulting chimera H1-2P₃H₄P5-6H7-8 was active, but only about 28% of wPU. Multiple sequence alignment and homology modeling predicted that mutations of E24D and E83G in H1-2P₃H₄P5-6H7-8 were favorable for further increase of its activity. After site-directed mutagenesis, H1-2P₃H₄P5-6H7-8 (E24D & E83G) with increased homology (91.45%) with dHU and higher activity and catalytic efficiency than the FDA-approved porcine-baboon chimera (PBC) was obtained. It showed optimum activity at pH 8.5 and 35 °C and was stable in a pH range of 6.5-11.0 and temperature range of 20-40 °C.