Single-cell analysis of the CD8+ T-cell compartment in multiple myeloma reveals disease specific changes are chiefly restricted to a CD69- subset suggesting potent cytotoxic effectors exist within the tumor bed.

Multiple myeloma (MM) is an incurable disease of the bone marrow (BM) characterized by the uncontrolled proliferation of neoplastic plasma cells. While CD8+ T cells have an established role in disease control, few studies have focused on these cells within the MM tumor microenvironment (TME). We analyzed CD8+ T cells in the BM and peripheral blood (PB) of untreated patients with MM and non-myeloma controls using flow cytometry, mass cytometry and single-cell RNA sequencing, using several novel bioinformatics workflows. Inter-tissue differences were most evident in the differential expression of Granzymes B and K, which were strongly associated with two distinct subsets of CD8+ T cells delineated by the expression of CD69, accounting for roughly 50% of BM-CD8+ T cells of all assessed cohorts. While few differences were observable between health and disease in the BM-restricted CD8CD69+ T-cell subset, the CD8+CD69- T-cell subset in the BM of untreated MM patients demonstrated increased representation of highly differentiated effector cells and evident compositional parallels between the PB, absent in age-matched controls, where a marked reduction of effector cells was observed. We demonstrate the transcriptional signature of BM-CD8+ T cells from patients with MM more closely resembles TCR-activated CD8+ T cells from age-matched controls than their resting counterparts.

Impact of biochar on the antibiotic resistome and associated microbial functions in rhizosphere and bulk soil in water-saving and flooding irrigated paddy fields.

The addition of biochar in paddies under the condition of water-saving irrigation can simultaneously achieve soil improvement and water conservation, but little is known about the role of these two regulations in mediating the fate of antibiotic resistome in paddy soils. Here, metagenomic analysis was conducted to investigate the effects and intrinsic mechanisms of biochar application and irrigation patterns on propagation of antibiotic resistance genes (ARGs) in paddy soils. The addition of biochar in paddy soil resulted in a reduction of approximately 1.32%-8.01% in the total absolute abundance of ARGs and 0.60%-22.09% in the numbers of ARG subtype. Compared with flooding irrigation, the numbers of detected ARG subtype were reduced by 1.60%-22.90%, but the total absolute abundance of ARGs increased by 0.06%-5.79% in water-saving irrigation paddy soils. Moreover, the combined treatments of flooding irrigation and biochar could significantly reduce the abundance of ARGs in paddy soils. The incremental antibiotic resistance in soil induced by water-saving irrigation was likewise mitigated by the addition of biochar. Correlation analyses indicated that, the differences in soil physicochemical properties under biochar addition or irrigation treatments contributed to the corresponding changes in the abundance of ARGs. Moreover, the variations of microbial community diversity, multidrug efflux abundance and transport system-related genes in paddy soil were also important for mediating the corresponding differences in the abundance of ARGs under the conditions of biochar addition or irrigation treatments. The findings of this study demonstrated the effectiveness of biochar application in mitigating antibiotic resistance in paddy soils. However, it also highlighted a potential concern relating to the elevated antibiotic resistance associated with water-saving irrigation in paddy fields. Consequently, these results contribute to a deeper comprehension of the environmental risks posed by ARGs in paddy soils.

Simulating soil salinity dynamics, cotton yield and evapotranspiration under drip irrigation by ensemble machine learning.

Cotton is widely used in textile, decoration, and industry, but it is also threatened by soil salinization. Drip irrigation plays an important role in improving water and fertilization utilization efficiency and ensuring crop production in arid areas. Accurate prediction of soil salinity and crop evapotranspiration under drip irrigation is essential to guide water management practices in arid and saline areas. However, traditional hydrological models such as Hydrus require more variety of input parameters and user expertise, which limits its application in practice, and machine learning (ML) provides a potential alternative. Based on a global dataset collected from 134 pieces of literature, we proposed a method to comprehensively simulate soil salinity, evapotranspiration (ET) and cotton yield. Results showed that it was recommended to predict soil salinity, crop evapotranspiration and cotton yield based on soil data (bulk density), meteorological factors, irrigation data and other data. Among them, meteorological factors include annual average temperature, total precipitation, year. Irrigation data include salinity in irrigation water, soil matric potential and irrigation water volume, while other data include soil depth, distance from dripper, days after sowing (for EC and soil salinity), fertilization rate (for yield and ET). The accuracy of the model has reached a satisfactory level, R2 in 0.78-0.99. The performance of stacking ensemble ML was better than that of a single model, i.e., gradient boosting decision tree (GBDT); random forest (RF); extreme gradient boosting regression (XGBR), with R2 increased by 0.02%-19.31%. In all input combinations, other data have a greater impact on the model accuracy, while the RMSE of the S1 scenario (input without meteorological factors) without meteorological data has little difference, which is -34.22%~19.20% higher than that of full input. Given the wide application of drip irrigation in cotton, we recommend the application of ensemble ML to predict soil salinity and crop evapotranspiration, thus serving as the basis for adjusting the irrigation schedule.

Salt tolerance evolution facilitates antibiotic resistome in soil microbiota: Evidences from dissemination evaluation, hosts identification and co-occurrence exploration.

Salinity is considered as one of the vital factors affecting the profiles of antibiotic resistance genes (ARGs) in soils, whereby its roles in shaping the antibiotic resistome were still poorly understood. Here, metagenomic analysis was conducted to track the ARGs distributions and dissemination in soils during salt accumulation and desalinization processes. Neutral-salt accumulation for 45 and 90 days significantly increased the relative abundances of ARGs and mobile genetic elements (MGEs) carrying antibiotic resistance contigs (ARCs). The ARGs within antibiotic efflux and target protection families primarily carried by Streptomyces, Nocardioides, Rhodanobacter and Monashia were largely enriched by salinity. The ARGs subtypes of the resistance-nodulation-division (RND) family, ATP-binding cassette (ABC) family, rRNA methyltransferase and other efflux were closely associated with MGEs, contributing to the enrichment of ARGs. Moreover, the ARGs subtypes and transposons were genetically linked with the salt-tolerance mechanisms of organic osmolyte transporters and K+ uptake proteins on the same ARC, demonstrating the coselection of ARGs and halotolerant genes. Furthermore, the antibiotic resistome could recover to a normal state after the prolonged incubation by alleviating salt stress. Nevertheless, the acquisition of ARGs by opportunistic pathogens after salt treatment was increased, serving to prioritize further efforts on the health risks correlated with resistance propagation and human exposure in saline soils.

Soil nitrogen functional transformation microbial genes response to biochar application in different irrigation paddy field in southern China.

Growing evidence points to the controlled irrigation (CI) and biochar application (BA) having agricultural economic value and ecological benefits, but their synergistic effect and microbial mechanism of nitrogen conversion remain unknown in paddy fields. The effects of different BA (0, 20, 40 t/hm2) on the soil nitrogen functional transformation microbial genes (nifH, AOA-amoA, AOB-amoA) in different irrigation (CI, flooding irrigation) were clarified. After one seasonal growth of paddy, the correlation between the abundance of functional genes OUT and soil nitrogen transformation environment factors during the typical growth period was analyzed. High-throughput sequencing results illustrated that the application of CC (40 t/hm2 biochar) increased the nifH genes bacterial community abundance; the abundance of dominant microorganism increased by 79.68~86.19%. Because biochar can potentially control the rates of N cycling in soil systems by adsorbing ammonia and increasing NH4+ storage, it increased soil NH4+-N and NO3--N content by 60.77% and 26.14%, improving microbial nitrogen fixation. Rare species Nitrosopumilus, Nitrosococcus, and Methylocystis appeared in biochar treatments group, which increased the diversity of microbial in paddy. The combined use of CI and BA affected soil inorganic nitrogen content, temperature (T), pH, Eh, etc., which affected urease, urea hydrolysis, and nitrogen functional transformation microorganism genes. Correlation analysis shows that soil NH4+-N, T, and Eh, respectively, are significant factors for the formation of nifH, AOA-amoA, and AOB-amoA soil bacterial communities, respectively. This study suggests that to maintain the biodiversity of soil and realize the sustainable development of rice cultivation, CI is of great importance in combination with BA.

Effect of Irrigation and Fertilizer Management on Rice Yield and Nitrogen Loss: A Meta-Analysis.

Irrigation and nitrogen fertilizer application are two important factors affecting yield and nitrogen loss in rice fields; however, the interaction effects of different irrigation schedules and combined management of nitrogen fertilizer application on yield and nitrogen loss in rice fields remain unknown. Therefore, we collected 327 sets of data on rice yield and 437 sets of data on nitrogen loss in rice fields from 2000 to 2021 and investigated the effects of different water-saving irrigation schedules, nitrogen application levels, and water-nitrogen couplings on rice yield, nitrogen use efficiency, and nitrogen loss (N2O emissions, nitrogen runoff, nitrogen leaching, and ammonia volatilization) by meta-analysis using conventional flooding irrigation and no nitrogen treatment as controls. The results showed that alternate wet and dry irrigation and controlled irrigation had increasing effects on rice yield. Alternate wet and dry irrigation had a significant yield-increasing effect (average 2.57% increase) and dry cultivation significantly reduced rice yield with an average 21.25% yield reduction. Water-saving irrigation reduces nitrogen runoff and leaching losses from rice fields but increases N2O emissions, and alternate wet and dry irrigation has a significant effect on increasing N2O emissions, with an average increase of 67.77%. Most water-saving irrigation can increase nitrogen use efficiency. Among water-saving irrigation methods, the effect of controlled irrigation on increasing nitrogen use efficiency is 1.06%. Rice yield and nitrogen use efficiency both showed a trend of increasing then decreasing with nitrogen fertilizer application, and nitrogen loss gradually increased with the amount of nitrogen fertilizer input. Water-nitrogen coupling management can significantly reduce nitrogen loss in rice fields while saving water and increasing yield. Based on the analysis of the data in this study, when the irrigation amount was 300~350 mm and the nitrogen application amount was 200~250 kg/ha, the rice yield and nitrogen fertilizer use efficiency were at a high level, which corresponded to the irrigation schedule of controlled irrigation or alternating wet and dry irrigation in the literature. However, different rice-growing areas are affected by rainfall and land capability, etc. Further optimization and correction of the adapted water and fertilizer management system for paddy fields are needed. The optimal water-nitrogen pattern of this study can achieve high rice yield and reduce nitrogen loss.

Evolving deep convolutional neural networks by IP-based marine predator algorithm for COVID-19 diagnosis using chest CT scans.

This paper proposes an optimal structured deep convolutional neural network (DCNN) based on the marine predator algorithm (MPA) to construct a novel automatic diagnosis platform that may help radiologists identify COVID-19 and non-COVID-19 patients based on CT scan categorization and analysis. The goal is met with the help of three modifications based on the regular MPA. First, a novel encoding scheme based on Internet Protocol (IP) addresses is proposed, followed by introducing an Enfeebled layer to build a variable-length DCNN. Finally, the learning process divides big datasets into smaller chunks that are randomly evaluated. The proposed model is compared to the COVID-CT and SARS-CoV-2 datasets to undertake a complete evaluation. Following that, the performance of the developed model (DCNN-IPMPA) is compared to that of a typical DCNN and seven variable-length models using five well-known comparison metrics, as well as the receiver operating characteristic and precision-recall curves. The results show that the DCNN-IPMPA outperforms other benchmarks, with a final accuracy of 97.21% on the SARS-CoV-2 dataset and 97.94% on the COVID-CT dataset. Also, timing analysis indicates that the DCNN processing time is the best among all benchmarks as expected; however, DCNN-IPMPA represents a competitive result compared to the standard DCNN.

Can ensemble machine learning be used to predict the groundwater level dynamics of farmland under future climate: a 10-year study on Huaibei Plain.

Accurate and simple prediction of farmland groundwater level (GWL) is an important aspect of agricultural water management. A farmland GWL prediction model, GWPRE, was developed that integrates four machine learning (ML) models (support vector machine regression, random forest, multiple perceptions, and the stacking ensemble model) with weather forecasts. Based on the GWL and meteorological data of five monitoring wells (N1, N2, N3, N4, and N5) in Huaibei plain from 2010 to 2020, the feasibility of predicting GWL by meteorological factors and ML algorithm was tested. In addition, the stacking ensemble model and future meteorological data after Bayesian model averaging were introduced for the first time to predict GWL under future climate conditions. The results showed that GWL showed an increasing trend in the past decade, but it will decrease in the future. The performance of the stacking ensemble model was better than that of any single ML model, with RMSE reduced by 4.26 ~ 96.97% and the running time reduced by 49.25 ~ 99.40%. GWL was most sensitive to rainfall, and the sensitivity index ranged from 0.2547 to 0.4039. The fluctuation range of GWL of N1, N2, and N3 was 1.5 ~ 2.5 m in the next decade. Due to the possible high rainfall, the GWL decreased in 2024 under RCP 2.6 and 2026 under RCP 8.5. It is worth noting that although the stacking ensemble model can improve the accuracy, it is not always the best among ML models in terms of portability. Nevertheless, the stacking ensemble model was recommended for GWL prediction under climate change.

Controlled release urea improves rice production and reduces environmental pollution: a research based on meta-analysis and machine learning.

To reveal the comprehensive impacts of controlled release urea (CRU) on rice production, nitrogen (N) loss, and greenhouse gas (GHG) emissions, a research based on global meta-analysis and machine learning (ML) was conducted. The results revealed that the CRU application instead of conventional fertilizer can increase rice yield, N use efficiency (NUE), and net benefits by 5.24%, 20.18%, and 9.30%, respectively, under the same amount of N. Furthermore, the emission of N2O and CH4, global warming potential (GWP), the loss of N leaching, and NH3 volatilization were respectively reduced by 25.64%, 18.33%, 21.10%, 14.90%, and 35.88%. The enhancing effects of CRU on rice yield and NUE were greater when the nitrogen application rate was 150 kg N ha-1. Nevertheless, the reducing effects of CRU on GHG emission reduction, nitrogen leaching, and NH3 volatilization was greater at high nitrogen application rate (≥150 kg ha-1). Mitigating effects of CRU on N2O and CH4 emission were significant when soil pH ≥ 6, while CRU posed a measurable effect on reducing nitrogen leaching and NH3 volatilization in paddy fields with soil organic carbon lower than 15 g kg-1 and pH lower than 6. Based on the data collected from meta-analysis, the results of ML demonstrated that it was feasible to use soil data and N application rate to predict N losses in rice fields under CRU. The performance of random forest is better than multilayer perceptron regression in predicting N losses from paddy fields. Thus, it is necessary to promote the application of CRU in paddy fields, especially in coarse soil, in which scenario the environmental pollution would be decreased and the rice yields, NUE, and net benefits would be increased. Meanwhile, machine learning models can be used to predict N losses in CRU paddy fields.

Antibiotic resistance genes alternation in soils modified with neutral and alkaline salts: interplay of salinity stress and response strategies of microbes.

Growing evidence points to the pivotal roles of salt accumulation in mediating antibiotic resistance genes (ARGs) spread in soil, whereas how salt mediates ARGs dissemination remains unknown. Herein, the effects of neutral or alkaline (Ne/Al) salt at low, moderate and high levels (Ne/Al-L, Ne/Al-M, Ne/Al-H) on the dissemination of ten typical ARGs in soils were explored, by simultaneously considering the roles of salinity stress and response strategies of microbes. In the soils amended with Ne/Al-L and Al-M salt, the dissemination of ARGs was negligible and the relative abundances of ARGs and mobile genetic elements (MGEs) were decreased. However, Ne-M and Al-H salt contributed to the dissemination of ARGs in soils, with the significantly increased absolute and relative abundances of ARGs and MGEs. In Ne-H soil, although the absolute abundance of ARGs declined drastically due to serious oxidative damage, their relative abundances were promoted. The facilitated ARGs transfer was potentially related to the excessive generation of intracellular reactive oxygen species and increased activities of DNA repair enzymes involved in SOS system. In addition, the activated intracellular protective response including quorum sensing and energy metabolism largely provided essential factors for ARGs dissemination. The co-occurrence of ARGs and over-expressed salt-tolerant genes in specific halotolerant bacteria further suggested the selection of salt stress on ARGs. Moreover, less disturbance of alkaline salt than neutral salt on ARGs evolution was observed, due to the lower abiotic stress and selective pressure on microbes. This study highlights that soil salinity-sodicity could dose-dependently reshape the dissemination of ARGs and community structure of microbes, which may increase the ecological risks of ARGs in agricultural environment.

COVID-19 Outbreak Caused by Contaminated Packaging of Imported Cold-Chain Products - Liaoning Province, China, July 2020.

What is known about this topic? Few major outbreaks of coronavirus disease 2019 (COVID-19) have occurred in China after major non-pharmaceutical interventions and vaccines have been deployed and implemented. However, sporadic outbreaks that had high possibility to be linked to cold chain products were reported in several cities of China.. What is added by this report? In July 2020, a COVID-19 outbreak occurred in Dalian, China. The investigations of this outbreak strongly suggested that the infection source was from COVID-19 virus-contaminated packaging of frozen seafood during inbound unloading personnel contact. What are the implications for public health practice? Virus contaminated paper surfaces could maintain infectivity for at least 17-24 days at -25 ℃. Exposure to COVID-19 virus-contaminated surfaces is a potential route for introducing the virus to a susceptible population. Countries with no domestic transmission of COVID-19 should consider introducing prevention strategies for both inbound travellers and imported goods. Several measures to prevent the introduction of the virus via cold-chain goods can be implemented.

Attenuation effects of iron on dissemination of antibiotic resistance genes in anaerobic bioreactor: Evolution of quorum sensing, quorum quenching and dynamics of community composition.

Zero valent iron (ZVI) coupled with bioreactors is arising as a promising technology for antibiotic resistance genes (ARGs) mitigation, whereas the succession and behaviors of microbes caused by ZVI in relieving ARGs propagation remain unclear. Herein, the effects of ZVI on microbial quorum sensing (QS), quorum quenching (QQ) system and community dynamics were examined in anaerobic bioreactor fed with oxytetracycline (tet), to illustrate the roles of evolutive microbial communication and community composition in ARGs attenuation. With the addition of 5 g/L ZVI, the total absolute abundance of tet ARGs was retarded by approximate 95% and 72% in sludge and effluent after 25 days operation. The abundance of mobile genetic elements and the heredity of antibiotic resistant bacteria revealed the declined horizontal and vertical transfer of ARGs, which directly led to the reduced ARGs propagation. Potential mechanisms are that the positive effects of ZVI on QQ activity via the functional bacteria enrichment inhibited QS system and thus ARGs transfer. Partial least--squares path modeling further demonstrated that ARGs abundance was strongly limited by the dynamics of bacterial composition and thereby less frequent microbial communication. These results provide new insights into the mechanisms of antibiotic resistome remission in anaerobic bioreactor modified by ZVI.

Antibiotic resistance genes attenuation in anaerobic microorganisms during iron uptake from zero valent iron: An iron-dependent form of homeostasis and roles as regulators.

Zero valent iron (ZVI) has been previously documented to attenuate the propagation of antibiotic resistance genes (ARGs) in microbes, while how ZVI affects the evolution of ARGs remains unclear. Herein, we investigated the influences of ZVI on ARGs dissemination in anaerobic bioreactor treating oxytetracycline (tet) containing wastewater, by deciphering the roles of iron homeostasis and regulatory effects. A net reduction of tet gene targets ranging from 0.75 to 1.88 and 0.67 to 2.08 log unit in intracellular and extracellular DNA was achieved at the optimal dosage of 5 g/L ZVI, whereas 20 g/L ZVI made no effects on ARGs reduction. The reduced ARGs abundance by ZVI was directly related to the inhibited horizontal transfer of ARGs and decreased proliferation of resistant strains (mainly Paludibacter and WCHB1-32). The potential mechanisms included the increased antioxidant capacity, the depressed efflux pump system and the weakened energy driving force by Fur regulon in microbes (especially for Cloacibacterium and Dechloromonas). The negligible influence of 20 g/L ZVI on ARGs reduction was ascribed to the iron-catalyzed oxidative damage and reduced physiological activity. This study firstly illustrated the potential relationships among activation of iron uptake regulator leading to protection against oxidative stress, alternation of physiological metabolisms and reduction of ARGs dissemination. This work extents our understanding about the priority of ZVI in mitigating ARGs proliferation and sheds light on its potential application in wastewater treatment plants.

Treg and Oligoclonal Expansion of Terminal Effector CD8+ T Cell as Key Players in Multiple Myeloma.

The classical paradigm of host-tumor interaction, i.e. elimination, equilibrium, and escape (EEE), is reflected in the clinical behavior of myeloma which progresses from the premalignant condition, Monoclonal Gammopathy of Unknown Significance (MGUS). Despite the role of other immune cells, CD4+ regulatory T cells (Treg) and cytotoxic CD8+ T cells have emerged as the dominant effectors of host control of the myeloma clone. Progression from MGUS to myeloma is associated with alterations in Tregs and terminal effector CD8+ T cells (TTE). These changes involve CD39 and CD69 expression, affecting the adenosine pathway and residency in the bone marrow (BM) microenvironment, together with oligoclonal expansion within CD8+ TTE cells. In this mini-review article, in the context of earlier data, we summarize our recent understanding of Treg involvement in the adenosine pathway, the significance of oligoclonal expansion within CD8+ TTE cells and BM-residency of CD8+ TTE cells in MGUS and newly diagnosed multiple myeloma patients.

Inverse relationship between oligoclonal expanded CD69- TTE and CD69+ TTE cells in bone marrow of multiple myeloma patients.

CD8+CD57+ terminal effector T (TTE) cells are a component of marrow-infiltrating lymphocytes and may contribute to the altered immune responses in multiple myeloma (MM) patients. We analyzed TTE cells in the bone marrow (BM) and peripheral blood (PB) of age-matched controls and patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering MM (SMM), and newly diagnosed (ND) MM using flow cytometry, mass cytometry, and FlowSOM clustering. TTE cells are heterogeneous in all subjects, with BM containing both CD69- and CD69+ subsets, while only CD69- cells are found in PB. Within the BM-TTE compartment, CD69- and CD69+ cells are found in comparable proportions in controls, while CD69- cells are dominant in MGUS and SMM and predominantly either CD69- or CD69+ cells in NDMM. A positive relationship between CD69+TTE and CD69-TTE cells is observed in the BM of controls, lost in MGUS, and converted to an inverse relationship in NDMM. CD69-TTE cells include multiple oligoclonal expansions of T-cell receptor/Vß families shared between BM and PB of NDMM. Oligoclonal expanded CD69-TTE cells from the PB include myeloma-reactive cells capable of killing autologous CD38hi plasma cells in vitro, involving degranulation and high expression of perforin and granzyme. In contrast to CD69-TTE cells, oligoclonal expansions are not evident within CD69+TTE cells, which possess low perforin and granzyme expression and high inhibitory checkpoint expression and resemble T resident memory cells. Both CD69-TTE and CD69+TTE cells from the BM of NDMM produce large amounts of the inflammatory cytokines interferon-γ and tumor necrosis factor α. The balance between CD69- and CD69+ cells within the BM-TTE compartment may regulate immune responses in NDMM and contribute to the clinical heterogeneity of the disease.

Effect of biochar addition on CO2 exchange in paddy fields under water-saving irrigation in Southeast China.

Biochar has been widely applied to paddy fields to improve soil fertility, crop productivity and carbon sequestration, thereby leading to variations in the CO2 exchange between the paddy fields under flooding irrigation and the atmosphere, as indicated by many previous reports. However, few relevant reports have focused on paddy fields under water-saving irrigation. This study conducted a field experiment to investigate the effects of three biochar addition rates (0, 20 and 40 t ha-1) on the CO2 exchange between paddy fields under controlled irrigation (CI, a water-saving irrigation technique) and the atmosphere in the Taihu Lake region of Southeast China. Our results showed that biochar addition increased the paddy field ecosystem respiration (Reco) and the soil respiration rate (Rs) in the CI paddy fields. And biochar application increased the total CO2 emissions and the total soil CO2 emissions, especially at a rate of 40 t ha-1. In contrast, gross primary productivity (GPP) was decreased and the net ecosystem exchange of CO2 (NEE) was increased with biochar addition. However, biochar addition at a rate of 20 t ha-1 significantly increased the total CO2 absorption and the net CO2 absorption of the CI paddy fields (p < 0.05), whereas biochar addition at a rate of 40 t ha-1 had no effect on the total CO2 absorption and decreased the total net CO2 absorption. At the same time, biochar addition significantly increased soil catalase, invertase and urease activities and contributed substantially to the increase in soil invertase activity. In addition, the soil bacterial, fungal and actinomycetal abundances were evidently increased with biochar addition, of which the soil fungal abundance showed the greatest increase. A high correlation was observed between soil catalase and invertase activities and soil microbial abundance. Reco was highly correlated with air and soil temperatures and soil enzyme activity. A significant quadratic polynomial correlation was observed between GPP and leaf area index (p < 0.01). The combination of biochar addition at a rate of 20 t ha-1 and water-saving irrigation has the potential to increase the size of the carbon sink and promote soil enzyme and microbial activities in paddy field ecosystems.

Effects of Biochar Application on Soil Organic Carbon Composition and Enzyme Activity in Paddy Soil under Water-Saving Irrigation.

Rice water-saving irrigation technology can remarkably reduce irrigation water input and maintain high yield; however, this technology can also accelerate the decomposition of soil organic matter in paddy fields. The spatial and temporal distributions of soil organic carbon (SOC), water-soluble organic carbon (WSOC), and soil microbial biomass carbon (SMBC) under different water-carbon regulation scenarios were analyzed on the basis of field experiments in the Taihu Lake region in China to explore the effects of biochar application on SOC and its components in water-saving irrigation paddy fields. The response of soil catalase (CAT) and invertase (INV) to biochar application in water-saving irrigated rice fields was clarified. The results showed that water-saving irrigation reduced the SOC content by 5.7% to 13.3% but increased WSOC and SMBC contents by 13.8% to 26.1% and 0.9% to 11.1%, respectively, as compared with flooding irrigation. Nonflooding management promoted the oxidative decomposition of soil organic matter. Two years after straw biochar was added, paddy soil SOC content under water-saving irrigation was increased by 4.0% to 26.7%. The WSOC and SMBC contents were also increased by 4.0% to 52.4% and 7.0% to 40.8%, respectively. The high straw biochar addition rate exhibited great impact on SOC. Remarkable correlations among SOC, WSOC, and SMBC were observed, indicating that the addition of straw biochar improved soil labile C, such as WSOC and SMBC, which promoted SOC transformation and stability in paddy soil under water-saving irrigation. Soil CAT and INV were related to SOC conversion. In conclusion, the combination of water-saving irrigation and straw biochar addition was beneficial to the improvement of soil properties and fertility of paddy fields.

Mass Cytometry Discovers Two Discrete Subsets of CD39-Treg Which Discriminate MGUS From Multiple Myeloma.

Multiple Myeloma (MM) is preceded by the clinically stable condition monoclonal gammopathy of undetermined significance (MGUS). Critical immune events that discriminate MGUS from newly diagnosed MM (ND)MM patients remain unknown, but may involve changes in the regulatory T cell (Treg) compartment that favor myeloma growth. To address this possibility, we used mass cytometry and the unsupervised clustering algorithm Flow self-organizing map (FlowSOM) to interrogate the distribution of multiple subsets within CD25+CD127low/negTreg in matched bone marrow (BM) and peripheral blood (PB) of MGUS and NDMM patients. Both mass cytometry and flow cytometry confirmed a trend toward prevalence of CD39-Treg within the Treg compartment in BM and PB of NDMM patients compared to CD39-Treg in MGUS patients. FlowSOM clustering displayed a phenotypic organization of Treg into 25 metaclusters that confirmed Treg heterogeneity. It identified two subsets which emerged within CD39-Treg of NDMM patients that were negligible or absent in CD39-Treg of MGUS patients. One subset was found in both BM and PB which phenotypically resembled activated Treg based on CD45RO, CD49d, and CD62L expression; another subset resembled BM-resident Treg based on its tissue-resident CD69+CD62L-CD49d- phenotype and restricted location within the BM. Both subsets co-expressed PD-1 and TIGIT, but PD-1 was expressed at higher levels on BM-resident Treg than on activated Treg. Within BM, both subsets had limited Perforin and Granzyme B production, whilst activated Treg in PB acquired high Perforin and Granzyme B production. In conclusion, the use of mass cytometry and FlowSOM clustering discovered two discrete subsets of CD39-Treg which are discordant in MGUS and NDMM patients and may be permissive of myeloma growth which warrants further study. Understanding the regulatory properties of these subsets may also advance MGUS and MM diagnosis, prognosis, and therapeutic implications for MM patients.