Proposed clinical phases for the improvement of personalized treatment of checkpoint inhibitor–related pneumonitis

BackgroundCheckpoint inhibitor–related pneumonitis (CIP) is a lethal immune-related adverse event. However, the development process of CIP, which may provide insight into more effective management, has not been extensively examined.MethodsWe conducted a multicenter retrospective analysis of 56 patients who developed CIP. Clinical characteristics, radiological features, histologic features, and laboratory tests were analyzed. After a comprehensive analysis, we proposed acute, subacute, and chronic phases of CIP and summarized each phase’s characteristics.ResultsThere were 51 patients in the acute phase, 22 in the subacute phase, and 11 in the chronic phase. The median interval time from the beginning of CIP to the different phases was calculated (acute phase: ≤4.9 weeks; subacute phase: 4.9~13.1 weeks; and chronic phase: ≥13.1 weeks). The symptoms relieved from the acute phase to the chronic phase, and the CIP grade and Performance Status score decreased (P<0.05). The main change in radiologic features was the absorption of the lesions, and 3 (3/11) patients in the chronic phase had persistent traction bronchiectasis. For histologic features, most patients had acute fibrinous pneumonitis in the acute phase (5/8), and most had organizing pneumonia in the subacute phase (5/6). Other histologic changes advanced over time, with the lesions entering a state of fibrosis. Moreover, the levels of interleukin-6, interleukin-10 and high-sensitivity C-reactive protein (hsCRP) increased in the acute phase and decreased as CIP progressed (IL-6: 17.9 vs. 9.8 vs. 5.7, P=0.018; IL-10: 4.6 vs 3.0 vs. 2.0, P=0.041; hsCRP: 88.2 vs. 19.4 vs. 14.4, P=0.005).ConclusionsThe general development process of CIP can be divided into acute, subacute, and chronic phases, upon which a better management strategy might be based devised

Research on the Corn Stover Image Segmentation Method via an Unmanned Aerial Vehicle (UAV) and Improved U-Net Network

The cover of corn stover has a significant effect on the emergence and growth of soybean seedlings. Detecting corn stover covers is crucial for assessing the extent of no-till farming and determining subsidies for stover return; however, challenges such as complex backgrounds, lighting conditions, and camera angles hinder the detection of corn stover coverage. To address these issues, this study focuses on corn stover and proposes an innovative method with which to extract corn stalks in the field, operating an unmanned aerial vehicle (UAV) platform and a U-Net model. This method combines semantic segmentation principles with image detection techniques to form an encoder–decoder network structure. The model utilizes transfer learning by replacing the encoder with the first five layers of the VGG19 network to extract essential features from stalk images. Additionally, it incorporates a concurrent bilinear attention module (CBAM) convolutional attention mechanism to improve segmentation performance for intricate edges of broken stalks. A U-Net-based semantic segmentation model was constructed specifically for extracting field corn stalks. The study also explores how different data sizes affect stalk segmentation results. Experimental results prove that our algorithm achieves 93.87% accuracy in segmenting and extracting corn stalks from images with complex backgrounds, outperforming U-Net, SegNet, and ResNet models. These findings indicate that our new algorithm effectively segments corn stalks in fields with intricate backgrounds, providing a technical reference for detecting stalk cover in not only corn but also other crops

Chirality transition in the epoxidation of (-)-alpha-pinene and successive hydrolysis studied by Raman optical activity and DFT

Characterization of the chirality evolution involved in chemical and biochemical reaction processes is extremely important to the understanding of the chiral catalysis mechanism. In this work, the chiral transition from the epoxidation of (-)-alpha-pinene to alpha-pinene oxide and successive hydrolysis to (-)-pinanediol has been studied as an archetype of the asymmetric catalysis by Raman optical activity (ROA) and the DFT calculation. Minor changes of the absolute configuration of the chiral products from (-)-alpha-pinene to (-)-pinanediol lead to the dramatic variation in ROA spectra indicating that the chirality is delocalized in the whole molecule rather than only concentrated on the chiral centers. The oxygen atom of alpha-pinene oxide contributes strong ROA signals while the two hydroxyl groups of (-)-pinanediol give no apparent contribution to the chirality in terms of ROA signals. Isolation of the two symmetric anisotropic invariants shows that the predominant contribution to the ROA signals stems from the electric dipole-magnetic dipole invariant, and the bond polarizability model is indeed found to be a good approximation for molecules composed of entirely axially-symmetric bonds in alpha-pinene oxide and (-)-pinanediol. This study demonstrates the feasibility of using ROA to sensitively monitor the variation of the chirality transition during the chiral reactions either in the chemical or biological system

Biofilms attached to Myriophyllum spicatum play a dominant role in nitrogen removal in constructed wetland mesocosms with submersed macrophytes: Evidence from N-15 tracking, nitrogen budgets and metagenomics analyses

The mechanisms behind nitrogen removal by the submersed macrophyte-biofilm complex in wetlands remain to be fully elucidated. This study investigated the role of Myriophyllum spicatum and the biofilm on their leaves in nitrogen removal in mesocosm experiments. N-15 tracking showed that 61.9% and 30% of the N-15, respectively, was removed from the system and assimilated by the macrophyte-biofilm complex after loading with 5.4 mg L-1 N-15 labelled NH4+ for 17 days. Nitrogen budget results showed that about 0.2%, 0.2% and 3.6% of the nitrogen were emitted as water-, HCl- and NaOH-soluble nitrogen-gas species, respectively. Bacteria (76.7-91.8%) were the predominant domain in all samples, followed by eukaryotes (8.0-23.0%), archaea and viruses. Network analyses showed that there were positive- and negative-correlative relationships among nitrogen-cycling genes and nitrifiers and denitrifiers. Our data highlight the important role of biofilm on submersed macrophytes for nitrogen removal

New xylose transporters support the simultaneous consumption of glucose and xylose in Escherichia coli

Abstract Glucose and xylose are two major components of lignocellulose. Simultaneous consumption of glucose and xylose is critical for engineered microorganisms to produce fuels and chemicals from lignocellulosic biomass. Although many production limitations have been resolved, glucose‐induced inhibition of xylose transport remains a challenge. In this study, a cell growth‐based screening strategy was designed to identify xylose transporters uninhibited by glucose. The glucose pathway was genetically blocked in Escherichia coli so that glucose functions only as an inhibitor and cells need xylose as the carbon source for survival. Through adaptive evolution, omics analysis and reverse metabolic engineering, a new phosphoenolpyruvate: carbohydrate phosphotransferase system (PTS) galactitol transporter (GalABC, encoded by EcolC_1640, EcolC_1641, and EcolC_1642 genes) that is not inhibited by glucose was identified. Inactivation of adenylate cyclase led to increased expression of the EcolC_1642 gene, and a point mutation in gene EcolC_1642 (N13S) further enhanced xylose transport. During the second round of gene mining, AraE and a new ABC transporter (AraFGH) of xylose were identified. A point mutation in the transcription regulator araC (L156I) caused increased expression of araE and araFGH genes without arabinose induction, and a point mutation in araE (D223Y) further enhanced xylose transport. These newly identified xylose transporters can support the simultaneous consumption of glucose and xylose and have potential use in producing chemicals from lignocellulose

Association Analysis of Single Nucleotide Polymorphisms in the 5′ Regulatory Region of the IL-6 Gene with Eimeria tenella Resistance in Jinghai Yellow Chickens

Interleukin 6 (IL-6) is an immunoregulatory cytokine involved in various inflammatory and immune responses. To investigate the effects of single nucleotide polymorphisms (SNPs) and haplotypes of IL-6 on resistance to Eimeria tenella (E. tenella), SNPs in the 5′ regulatory region of IL-6 were detected with direct sequencing, and the effects of SNPs and haplotypes on resistance to E. tenella were analyzed by the least square model in Jinghai yellow chickens. Nineteen SNPs were identified in the 5′ regulation region of IL-6, among which three SNPs were newly discovered. The SNP association analysis results showed that nine of the SNPs were significantly associated with E. tenella resistance indexes; the A-483G locus was significantly associated with the GSH-Px, IL-2, and IL-17 indexes (p < 0.05); the C-447G locus was significantly associated with the SOD, GSH-Px, IL-17, and IL-2 indexes (p < 0.05); and the G-357A locus had significant effects on the CAT and IL-16 indexes (p < 0.05). Haplotype analysis showed that H2H3 and H2H5 were favorable haplotype combinations with good coccidium resistance. Furthermore, we used qRT-PCR and observed that the expression of IL-6 in the infection group was higher than that in the control group in the liver, proventriculus, small intestine, thymus, kidney, and bursa of Fabricius and extremely significantly different than that in the cecum especially (p < 0.01). In summary, SNPs and haplotypes in the 5′ regulatory region of IL-6 have important effects on E. tenella resistance, and the results will provide a reference for molecular marker selection of E. tenella resistance in Jinghai yellow chickens