Synthetic microbial communities: Sandbox and blueprint for soil health enhancement.

We summarize here the use of SynComs in improving various dimensions of soil health, including fertility, pollutant removal, soil-borne disease suppression, and soil resilience; as well as a set of useful guidelines to assess and understand the principles for designing SynComs to enhance soil health. Finally, we discuss the next stages of SynComs applications, including highly diverse and multikingdom SynComs targeting several functions simultaneously.

Information extraction of UV-NIR spectral data in waste water based on Large Language Model.

In recent years, with the rise of various machine learning methods, the Ultraviolet and Near Infrared (UV-NIR) spectral analysis has been impressive in the determination of intricate systems. However, the UV-NIR spectral analysis based on traditional machine learning requires independent training with tedious parameter tuning for different samples or tasks. As a result, training a high-quality model is often complicated and time-consuming. Large language model (LLM) is one of the cutting-edge achievements in deep learning, with the parameter size of the order of billion. LLM can extract abstract information from input and use it effectively. Even without any additional training, using only simple natural language prompts, LLM can accomplish tasks that have never been seen before in completely new domains. We look forward to utilizing this capability in spectral analysis to reduce the time-consuming and operational difficulties. In this study, we used UV-NIR spectral analysis to predict the concentration of Chemical Oxygen Demand (COD) in three different water samples, including a complex wastewater. By extracting the characteristic bands in the spectrum, we input them into LLM for concentration prediction. We compared the COD prediction results of different models on water samples and discussed the effects of different experiments setting on LLM. The results show that even with brief prompts, the prediction of LLM in wastewater achieved the best performance, with R2 and RMSE equal to 0.931 and 10.966, which exceed the best results of traditional models, where R2 and RMSE correspond to 0.920 and 11.854. This result indicates that LLM, with simpler operation and less time-consuming, has ability to approach or even surpass traditional machine learning models in UV-NIR spectral analysis. In conclusion, our study proposed a new method for the UV-NIR spectral analysis based on LLM and preliminary demonstrated the potential of LLM for application.

Hydroxygenkwanin suppresses peritoneal metastasis in colorectal cancer by modulating tumor-associated macrophages polarization.

Peritoneal metastasis is an important cause of high mortality and poor prognosis in colorectal cancer (CRC) patients. Therefore, the development of compounds with unique anti-CRC Peritoneal metastasis activities is urgently needed to improve the survival of CRC patients. Hydroxygenkwanin (HGK),a natural flavonoid compound, have been shown to display anti-inflammatory, antioxidant, antitumor, and immunoregulatory effects. Here, we employed CRC peritoneal metastasis mouse model with MC38 cells to examine the antitumor activity of HGK. The result showed that HGK not only inhibited peritoneal metastasis, but also significantly increased the proportion of M1-like macrophages while decreasing the proportion of M2-like macrophages within the tumor microenvironment (TME). Furthermore, we demonstrated that the inhibitory effect of HGK on peritoneal metastasis of CRC depended on macrophages in vitro and in vivo. Moreover, we revealed that HGK promoted the polarization of TAMs into M1-like macrophages and inhibited their polarization into M2-like macrophages in a LPS- or IL-4-induced bone marrow-derived macrophages (BMDMs) model and co-culture system. Finally, we also investigated the regulatory mechanism of HGK on TAMs polarization that HGK may active p-STAT5, p-NF-κB signaling in M1-like macrophages and inhibit p-STAT6, JMJD3, PPARγ expression in M2-like macrophages. Taken together, our findings suggest that HGK is a natural candidate for effective prevention of peritoneal metastasis in colorectal cancer, which provides a potential strategy for clinical treatment of colorectal cancer.

Novel insights into dimethylsulfoniopropionate cleavage by deep subseafloor fungi.

Dimethylsulfoniopropionate (DMSP), a key organic sulfur compound in marine and subseafloor sediments, is degraded by phytoplankton and bacteria, resulting in the release of the climate-active volatile gas dimethylsulfide (DMS). However, it remains unclear if dominant eukaryotic fungi in subseafloor sediments possess specific abilities and metabolic mechanisms for DMSP degradation and DMS formation. Our study provides the first evidence that fungi from coal-bearing sediments ∼2 km below the seafloor, such as Aspergillus spp., Chaetomium globosum, Cladosporium sphaerospermum, and Penicillium funiculosum, can degrade DMSP and produce DMS. In Aspergillus sydowii 29R-4-F02, which exhibited the highest DMSP-dependent DMS production rate (16.95 pmol/µg protein/min), two DMSP lyase genes, dddP and dddW, were identified. Remarkably, the dddW gene, previously observed only in bacteria, was found to be crucial for fungal DMSP cleavage. These findings not only extend the list of fungi capable of degrading DMSP, but also enhance our understanding of DMSP lyase diversity and the role of fungi in DMSP decomposition in subseafloor sedimentary ecosystems.

[Screw versus Kirschner wire fixation for lateral humeral condyle fractures in children:a meta analysis].

OBJECTIVE: To compare screw versus Kirschner wire fixation in the treatment of lateral humeral condyle fractures in children. METHODS: A systematic search was conducted in PubMed, Embase, the Cochrane library, Web of Science, China National Knowledge Internet(CNKI), Wanfang Datebase from in ception to February 2022. Studies comparing screws and Kirschner wire fixation in the treatment of lateral humeral condyle fractures in children were included. Outcome measures included and excluded by a set of inclusion and exclusion criteria and evaluated for their quality, their excellent and good rate of fracture healing, malunion, delayed union or nonunion, infection, limitation of elbow flexion or extension(>10°) were extracted and analyzed using software Rev Man 5.3. RESULTS: A total of 9 retrospective studies involving 647 patients were included, with 255 patients in the screw fixation group(including screw combined with Kirschner wire) and 392 patients in the Kirschner wire fixation group. Meta analysis showed the following:infection rate in the screw group was significantly lower than that in the Kirschner wire group[OR=0.22, 95%CI(0.09, 0.56), P=0.001]. There were no significant differences between the 2 groups in excellent and good rate of fracture healing, malunion rate(P>0.05). Subgroup analysis showed that infection rate in the screw-only group was significantly lower than that in the Kirschner wire group[OR=0.18, 95%CI(0.05, 0.65), P=0.009]. CONCLUSION: For lateral humeral condyle fractures, Screw fixation alone had a lower infection rate than kirschner wire fixation and screw combined with Kirschner wire fixation. There were no significant differences in the excellent and good rate of fracture healing, malunion. In terms of postoperative efficacy and safety of internal fixation, orthopaedic surgeons are more likely to recommend screws for fixation of lateral humeral condyle fractures in children.

Analysis of the impact of temperature on the spectral shift in ultraviolet hyperspectral imaging spectrometers.

The imaging spectrometer's high performance in practical applications may be compromised by environmental factors, particularly temperature variations, posing a challenge to its stability. Temperature fluctuations can induce spectral shift, directly impacting the accuracy of spectral measurements, subsequently influencing the precision of radiometric measurements. To address this issue, this study investigates a dual-channel UV imaging spectrometer. This instrument boasts a wavelength calibration accuracy of 0.01 nm. This paper conducts an in-depth analysis of the various mechanisms through which temperature changes influence the spectral line offset in the imaging spectrometer, integrating actual orbital temperature data to discuss the instrument's temperature load settings. The impact of temperature on spectral shift is examined using finite element analysis and optical design software. Estimations of spectral shift were made based on temperature variations. Simulation results indicated that the maximum deviation of spectral shift is estimated at 0.018 nm under a temperature condition of 16 ± 1°C. Under a more controlled orbital temperature condition (16 ± 0.3°C), the maximum deviation of spectral shift decreased to 0.01 nm. Experimental data revealed that at 16 ± 1°C, the maximum deviation of spectral shift did not exceed 0.01 nm. This effectively corroborates our theoretical analysis. The relationship between temperature and spectral shift offers a crucial theoretical foundation for calibrating spectral measurements and managing the thermal conditions of the instrument.

Biomechanical properties of articular cartilage in different regions and sites of the knee joint: acquisition of osteochondral allografts.

Osteochondral allograft (OCA) transplantation involves grafting of natural hyaline cartilage and supporting subchondral bone into the cartilage defect area to restore its biomechanical and tissue structure. However, differences in biomechanical properties and donor-host matching may impair the integration of articular cartilage (AC). This study analyzed the biomechanical properties of the AC in different regions of different sites of the knee joint and provided a novel approach to OCA transplantation. Intact stifle joints from skeletally mature pigs were collected from a local abattoir less than 8 h after slaughter. OCAs were collected from different regions of the joints. The patella and the tibial plateau were divided into medial and lateral regions, while the trochlea and femoral condyle were divided into six regions. The OCAs were analyzed and compared for Young's modulus, the compressive modulus, and cartilage thickness. Young's modulus, cartilage thickness, and compressive modulus of OCA were significantly different in different regions of the joints. A negative correlation was observed between Young's modulus and the proportion of the subchondral bone (r = - 0.4241, P < 0.0001). Cartilage thickness was positively correlated with Young's modulus (r = 0.4473, P < 0.0001) and the compressive modulus (r = 0.3678, P < 0.0001). During OCA transplantation, OCAs should be transplanted in the same regions, or at the closest possible regions to maintain consistency of the biomechanical properties and cartilage thickness of the donor and recipient, to ensure smooth integration with the surrounding tissue. A 7 mm depth achieved a higher Young's modulus, and may represent the ideal length.

Two aquaporins, PIP1;1 and PIP2;1, mediate the uptake of neonicotinoid pesticides in plants.

Neonicotinoids (NEOs), a large class of organic compounds, are a type of commonly used pesticide for crop protection. Their uptake and accumulation in plants are prerequisites for their intra- and intercellular movements, transformation, and function. Understanding the molecular mechanisms that underpin NEO uptake by plants is crucial for effective application, which remains elusive. Here, we demonstrate that NEOs enter plant cells primarily through the transmembrane symplastic pathway and accumulate mainly in the cytosol. Two plasma membrane intrinsic proteins discovered in Brassica rapa, BraPIP1;1 and BraPIP2;1, were found to encode aquaporins (AQPs) that are highly permeable to NEOs in different plant species and facilitate NEO subcellular diffusion and accumulation. Their conserved transport function was further demonstrated in Xenopus laevis oocyte and yeast assays. BraPIP1;1 and BraPIP2;1 gene knockouts and interaction assays suggested that their proteins can form functional heterotetramers. Assessment of the potential of mean force indicated a negative correlation between NEO uptake and the energy barrier of BraPIP1;1 channels. This study shows that AQPs transport organic compounds with greater osmolarity than previously thought, providing new insight into the molecular mechanisms of organic compound uptake and facilitating innovations in systemic pesticides.

PRMT1-mediated PGK1 arginine methylation promotes colorectal cancer glycolysis and tumorigenesis.

Many types of cancer cells, including colorectal cancer cells (CRC), can simultaneously enhance glycolysis and repress the mitochondrial tricarboxylic acid (TCA) cycle, which is called the Warburg effect. However, the detailed mechanisms of abnormal activation of the glycolysis pathway in colorectal cancer are largely unknown. In this study, we reveal that the protein arginine methyltransferase 1 (PRMT1) promotes glycolysis, proliferation, and tumorigenesis in CRC cells. Mechanistically, PRMT1-mediated arginine asymmetric dimethylation modification of phosphoglycerate kinase 1 (PGK1, the first ATP-producing enzyme in glycolysis) at R206 (meR206-PGK1) enhances the phosphorylation level of PGK1 at S203 (pS203-PGK1), which inhibits mitochondrial function and promotes glycolysis. We found that PRMT1 and meR206-PGK1 expression were positively correlated with pS203-PGK1 expression in tissues from colorectal cancer patients. Furthermore, we also confirmed that meR206-PGK1 expression is positively correlated with the poor survival of patients with colorectal cancer. Our findings show that PRMT1 and meR206-PGK1 may become promising predictive biomarkers for the prognosis of patients with CRC and that arginine methyltransferase inhibitors have great potential in colorectal cancer treatment.

Design of Light-Driven Biocompatible and Biodegradable Microrobots Containing Mg-Based Metallic Glass Nanowires.

Light-driven microrobots capable of moving rapidly on water surfaces in response to external stimuli are widely used in a variety of fields, such as drug delivery, remote sampling, and biosensors. However, most light-driven microrobots use graphene and carbon nanotubes as photothermal materials, resulting in poor biocompatibility and degradability, which greatly limits their practical bioapplications. To address this challenge, a composition and microstructure design strategy with excellent photothermal properties suitable for the fabrication of light-driven microrobots was proposed in this work. The Mg-based metallic glass nanowires (Mg-MGNWs) were embedded with polyhydroxyalkanoates (PHA) to fabricate biocompatible and degradable microrobots with excellent photothermal effect and complex shapes. Consequently, the microrobot can be precisely driven by a near-infrared laser to achieve high efficiency and remote manipulation on the water surface for a long period of time, with a velocity of 9.91 mm/s at a power density of 2.0 W/cm2. Due to the Marangoni effect, programmable and complex motions of the microrobot such as linear, clockwise, counterclockwise, and obstacle avoidance motions can be achieved. The biocompatible and degradable microrobot fabrication strategy could have great potential in the fields of environmental detection, targeted drug delivery, disease diagnosis, and detection.

E2F7 serves as a potential prognostic biomarker for lung adenocarcinoma.

E2F transcription factors (E2Fs) are a family of transcription factors critical regulators of the cell cycle, apoptosis, and differentiation, thus influencing tumorigenesis. However, the specific roles of E2Fs in lung adenocarcinoma (LUAD) remain unclear. Data from The Cancer Genome Atlas (TCGA) were used. R version. 4.0.3 and multiple databases (TIMER, cBioportal, gene expression profile interaction analysis [GEPIA], LinkedOmics, and CancerSEA) were utilized to investigate mRNA expression, mutational analysis, prognosis, clinical correlations, co-expressed gene, pathway and network, and single-cell analyses. Immunohistochemistry (IHC) confirmed that E2F transcription factor 7 (E2F7) correlated with LUAD. Among the E2Fs, E2F7 was identified by constructing a prognostic model most significantly associated with overall survival (OS) in LUAD patients. The univariate and multivariate Cox regression analyses showed that E2F7, p-T stage, and p-TNM stage were closely related to OS and progression-free survival (PFS) (P < .05) in LUAD. E2F 7/8 were also identified as significantly associated with tumor stage in the GEPIA database. Compared with paracancerous tissues, E2F7 was up-regulated in LUAD by IHC, and E2F7 might be positively correlated with larger tumors and higher TNM stages. E2F7 may primarily regulate DNA repair, damage, and cell cycle processes and thus affect LUAD tumorigenesis, invasion, and metastasis by LinkedOmics and CancerSEA. E2F7 serves as a potential prognostic biomarker for LUAD.

Lack of S1PR2 in Macrophage Ameliorates Sepsis-associated Lung Injury through Inducing IL-33-mediated Type 2 Immunity.

The function of type 2 immunity and mechanisms underlying the initiation of type 2 immunity after sepsis-induced lung injury remain unclear. Sphingosine-1-phosphate receptor 2 (S1PR2) has been demonstrated to modulate type 2 immunity in the context of asthma and pulmonary fibrosis. Thus, this study aims to investigate the role of type 2 immunity and whether and how S1PR2 regulates type 2 immunity in sepsis. Peripheral type 2 immune responses in patients with sepsis and healthy control subjects were assessed. The impact of S1PR2 on type 2 immunity in patients with sepsis and in a murine model of sepsis was further investigated. The type 2 innate immune responses were significantly increased in the circulation of patients 24 hours after sepsis, which was positively related to clinical complications and negatively correlated with S1PR2 mRNA expression. Animal studies showed that genetic deletion or pharmacological inhibition of S1PR2 induced type 2 innate immunity accumulation in the post-septic lungs. Mechanistically, S1PR2 deficiency promoted macrophage-derived interleukin (IL)-33 increase and the associated type 2 response in the lung. Furthermore, S1PR2-regulated IL-33 from macrophages mitigated lung injury after sepsis in mice. In conclusion, a lack of S1PR2 modulates the type 2 immune response by upregulating IL-33 release from macrophages and alleviates sepsis-induced lung injury. Targeting S1PR2 may have potential therapeutic value for sepsis treatment.

Deep learning for fast super-resolution ultrasound microvessel imaging.

Objective. Ultrasound localization microscopy (ULM) enables microvascular reconstruction by localizing microbubbles (MBs). Although ULM can obtain microvascular images that are beyond the ultimate resolution of the ultrasound (US) diffraction limit, it requires long data processing time, and the imaging accuracy is susceptible to the density of MBs. Deep learning (DL)-based ULM is proposed to alleviate these limitations, which simulated MBs at low-resolution and mapped them to coordinates at high-resolution by centroid localization. However, traditional DL-based ULMs are imprecise and computationally complex. Also, the performance of DL is highly dependent on the training datasets, which are difficult to realistically simulate.Approach. A novel architecture called adaptive matching network (AM-Net) and a dataset generation method named multi-mapping (MMP) was proposed to overcome the above challenges. The imaging performance and processing time of the AM-Net have been assessed by simulation andin vivoexperiments.Main results. Simulation results show that at high density (20 MBs/frame), when compared to other DL-based ULM, AM-Net achieves higher localization accuracy in the lateral/axial direction.In vivoexperiment results show that the AM-Net can reconstruct ∼24.3µm diameter micro-vessels and separate two ∼28.3µm diameter micro-vessels. Furthermore, when processing a 128 × 128 pixels image in simulation experiments and an 896 × 1280 pixels imagein vivoexperiment, the processing time of AM-Net is ∼13 s and ∼33 s, respectively, which are 0.3-0.4 orders of magnitude faster than other DL-based ULM.Significance. We proposes a promising solution for ULM with low computing costs and high imaging performance.

Foliar Spraying of Chlorpyrifos Triggers Plant Production of Linolenic Acid Recruiting Rhizosphere Bacterial Sphingomonas sp.

Plants have developed an adaptive strategy for coping with biotic or abiotic stress by recruiting specific microorganisms from the soil pool. Recent studies have shown that the foliar spraying of pesticides causes oxidative stress in plants and leads to changes in the rhizosphere microbiota, but the mechanisms by which these microbiota change and rebuild remain unclear. Herein, we provide for the first-time concrete evidence that rice plants respond to the stress of application of the insecticide chlorpyrifos (CP) by enhancing the release of amino acids, lipids, and nucleotides in root exudates, leading to a shift in rhizosphere bacterial community composition and a strong enrichment of the genus Sphingomonas sp. In order to investigate the underlying mechanisms, we isolated a Sphingomonas representative isolate and demonstrated that it is both attracted by and able to consume linolenic acid, one of the root exudates overproduced after pesticide application. We further show that this strain selectively colonizes roots of treated plants and alleviates pesticide stress by degrading CP and releasing plant-beneficial metabolites. These results indicate a feedback loop between plants and their associated microbiota allowing to respond to pesticide-induced stress.

Development and clinical validation of a microfluidic-based platform for CTC enrichment and downstream molecular analysis.

Background: Although many CTC isolation and detection methods can provide information on cancer cell counts, downstream gene and protein analysis remain incomplete. Therefore, it is crucial to develop a technology that can provide comprehensive information on both the number and profile of CTC. Methods: In this study, we developed a novel microfluidics-based CTC separation and enrichment platform that provided detailed information about CTC. Results: This platform exhibits exceptional functionality, achieving high rates of CTC recovery (87.1%) and purification (∼4 log depletion of WBCs), as well as accurate detection (95.10%), providing intact and viable CTCs for downstream analysis. This platform enables successful separation and enrichment of CTCs from a 4 mL whole-blood sample within 15 minutes. Additionally, CTC subtypes, selected protein expression levels on the CTC surface, and target mutations in selected genes can be directly analyzed for clinical utility using immunofluorescence and real-time polymerase chain reaction, and the detected PD-L1 expression in CTCs is consistent with immunohistochemical assay results. Conclusion: The microfluidic-based CTC enrichment platform and downstream molecular analysis together provide a possible alternative to tissue biopsy for precision cancer management, especially for patients whose tissue biopsies are unavailable.

Deep learning for fast denoising filtering in ultrasound localization microscopy.

Objective.Addition of a denoising filter step in ultrasound localization microscopy (ULM) has been shown to effectively reduce the error localizations of microbubbles (MBs) and achieve resolution improvement for super-resolution ultrasound (SR-US) imaging. However, previous image-denoising methods (e.g. block-matching 3D, BM3D) requires long data processing times, making ULM only able to be processed offline. This work introduces a new way to reduce data processing time through deep learning.Approach.In this study, we propose deep learning (DL) denoising based on contrastive semi-supervised network (CS-Net). The neural network is mainly trained with simulated MBs data to extract MB signals from noise. And the performances of CS-Net denoising are evaluated in bothin vitroflow phantom experiment andin vivoexperiment of New Zealand rabbit tumor.Main results.Forin vitroflow phantom experiment, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of single microbubble image are 26.91 dB and 4.01 dB, repectively. Forin vivoanimal experiment , the SNR and CNR were 12.29 dB and 6.06 dB. In addition, single microvessel of 24µm and two microvessels separated by 46µm could be clearly displayed. Most importantly,, the CS-Net denoising speeds forin vitroandin vivoexperiments were 0.041 s frame-1and 0.062 s frame-1, respectively.Significance.DL denoising based on CS-Net can improve the resolution of SR-US as well as reducing denoising time, thereby making further contributions to the clinical real-time imaging of ULM.

Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer.

Background: The tumour-node-metastasis (TNM) staging system is insufficient to precisely distinguish the long-term survival of patients who underwent pneumonectomy for primary lung cancer. Therefore, this study sought to identify determinants of disease-free (DFS) and overall survival (OS) for incorporation into web-based dynamic nomograms. Methods: The clinicopathological variables, surgical methods and follow-up information of 1,261 consecutive patients who underwent pneumonectomy for primary lung cancer between January 2008 and December 2018 at Sun Yat-sen University Cancer Center were collected. Nomograms for predicting DFS and OS were built based on the significantly independent predictors identified in the training cohort (n = 1,009) and then were tested on the validation cohort (n = 252). The concordance index (C-index) and time-independent area under the receiver-operator characteristic curve (AUC) assessed the nomogram's discrimination accuracy. Decision curve analysis (DCA) was applied to evaluate the clinical utility. Results: During a median follow-up time of 40.5 months, disease recurrence and death were observed in 446 (35.4%) and 665 (52.7%) patients in the whole cohort, respectively. In the training cohort, a higher C-reactive protein to albumin ratio, intrapericardial pulmonary artery ligation, lymph node metastasis, and adjuvant therapy were significantly correlated with a higher risk for disease recurrence; similarly, the independent predictors for worse OS were intrapericardial pulmonary artery and vein ligation, higher T stage, lymph node metastasis, and no adjuvant therapy. In the validation cohort, the integrated DFS and OS nomograms showed well-fitted calibration curves and yielded good discrimination powers with C-index of 0.667 (95% confidence intervals CIs [0.610-0.724]) and 0.697 (95% CIs [0.649-0.745]), respectively. Moreover, the AUCs for 1-year, 3-year, and 5-year DFS were 0.655, 0.726, and 0.735, respectively, and those for 3-year, 5-year, and 10-year OS were 0.741, 0.765, and 0.709, respectively. DCA demonstrated that our nomograms could bring more net benefit than the TNM staging system. Conclusions: Although pneumonectomy for primary lung cancer has brought encouraging long-term outcomes, the constructed prediction models could assist in precisely identifying patients at high risk and developing personalized treatment strategies to further improve survival.

The potential role of subseafloor fungi in driving the biogeochemical cycle of nitrogen under anaerobic conditions.

Fungi represent the dominant eukaryotic group of organisms in anoxic marine sedimentary ecosystems, ranging from a few centimeters to ~ 2.5 km below seafloor. However, little is known about how fungi can colonize anaerobic subseafloor environments for tens of millions of years and whether they play a role in elemental biogeochemical cycles. Based on metabolite detection, isotope tracer and gene analysis, we examined the anaerobic nitrogen conversion pathways of 19 fungal species (40 strains) isolated from1.3 to 2.5 km coal-bearing sediments below seafloor. Our results show for the first time that almost all fungi possess anaerobic denitrification, dissimilatory nitrate reduction to ammonium (DNRA), and nitrification pathways, but not anaerobic ammonium oxidation (anammox). Moreover, the distribution of fungi with different nitrogen-conversion abilities in subseafloor sediments was mainly determined by in situ temperature, CaCO3, and inorganic carbon contents. These findings suggest that fungi have multiple nitrogen transformation processes to cope with their requirements for a variety of nitrogen sources in nutrient deficient anaerobic subseafloor sedimentary environments.

Chemotherapy for advanced pulmonary sarcomatoid carcinoma: a population-based propensity score matching study.

OBJECTIVES: Pulmonary sarcomatoid carcinoma (PSC) is a rare histological type of non-small cell lung cancer (NSCLC). There are no specific treatment guidelines for PSC. For advanced PSC (stage II-IV), the role of chemotherapy is still controversial. The purpose of this study was to investigate the effect of chemotherapy on the prognosis of advanced PSC. METHODS: A total of 960 patients with advanced PSC from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2019 were enrolled in this study. To investigate the prognostic factors, the Cox proportional hazard regression model was conducted. A total of 642 cases were obtained after propensity score matching (PSM). The Kaplan‒Meier method was applied to compare overall survival (OS) and cancer-specific survival (CSS). RESULTS: For all 960 cases included in this study, the Cox proportional hazard model was applied for prognostic analysis. Univariate and multivariate analyses showed that stage, T stage, N stage, M stage, surgery, and chemotherapy were prognostic factors for OS and CSS (P < 0.05). A total of 642 cases were obtained after PSM, with no significant difference between the two groups for all variables. Kaplan‒Meier curves indicated that for OS and CSS, the prognosis was significantly better in the chemotherapy group than in the no-chemotherapy group. CONCLUSIONS: For advanced PSC, chemotherapy can significantly improve the OS and CSS of patients. Chemotherapy should be an important part of PSC treatment.

Functional characterization of rice (Oryza sativa) thioredoxins for detoxification and degradation of atrazine.

Thioredoxins (TRXs) are a group of antioxidant enzymes that play a critical role in plant growth and resistance to stress. However, the functional role and mechanism of rice TRXs in response to pesticides (e.g. atrazine, ATZ) stress remain largely unexplored. Here, 24 differentially expressed TRX genes (14 up and 10 down) of ATZ-exposed rice were identified through high-throughput RNA-sequencing analysis. Twenty-four TRX genes were unevenly mapped to 11 chromosomes and some of the genes were validated by quantitative RT-PCR. Bioinformatics analysis revealed that ATZ-responsive TRX genes contain multiple functional cis-elements and conserved domains. To demonstrate the functional role of the genes in ATZ degradation, one representative TRX gene LOC_Os07g08840 was transformed into yeast cells and observed significantly lower ATZ content compared to the control. Using LC-Q-TOF-MS/MS, five metabolites were characterized. One hydroxylation (HA) and two N-dealkylation products (DIA and DEA) were significantly increased in the medium with positive transformants. Our work indicated that TRX-coding genes here were responsible for ATZ degradation, suggesting that thioredoxins could be one of the vital strategies for pesticide degradation and detoxification in crops.