Insights from high-fidelity modeling of industrial rotary bell atomization.

The global automotive industry sprayed over 2.6 billion liters of paint in 2018, much of which through electrostatic rotary bell atomization, a highly complex process involving the fluid mechanics of rapidly rotating thin films tearing apart into micrometer-thin filaments and droplets. Coating operations account for 65% of the energy usage in a typical automotive assembly plant, representing 10,000s of gigawatt-hours each year in the United States alone. Optimization of these processes would allow for improved robustness, reduced material waste, increased throughput, and significantly reduced energy usage. Here, we introduce a high-fidelity mathematical and algorithmic framework to analyze rotary bell atomization dynamics at industrially relevant conditions. Our approach couples laboratory experiment with the development of robust non-Newtonian fluid models; devises high-order accurate numerical methods to compute the coupled bell, paint, and gas dynamics; and efficiently exploits high-performance supercomputing architectures. These advances have yielded insight into key dynamics, including i) parametric trends in film, sheeting, and filament characteristics as a function of fluid rheology, delivery rates, and bell speed; ii) the impact of nonuniform film thicknesses on atomization performance; and iii) an understanding of spray composition via primary and secondary atomization. These findings result in coating design principles that are poised to improve energy- and cost-efficiency in a wide array of industrial and manufacturing settings.

Phytophthora sojae Effector PsCRN108 Targets CAMTA2 to Suppress HSP40 Expression and ROS Burst.

Oomycete pathogens secrete numerous crinkling and necrosis proteins (CRNs) to manipulate plant immunity and promote infection. However, the functional mechanism of CRN effectors is still poorly understood. Previous research has shown that the Phytophthora sojae effector PsCRN108 binds to the promoter of HSP90s and inhibits their expression, resulting in impaired plant immunity. In this study, we found that in addition to HSP90, PsCRN108 also suppressed other Heat Shock Protein (HSP) family genes, including HSP40. Interestingly, PsCRN108 inhibited the expression of NbHSP40 through its promoter, but did not directly bind to its promoter. Instead, PsCRN108 interacted with NbCAMTA2, a negative regulator of plant immunity. NbCAMTA2 was a negative regulator of NbHSP40 expression, and PsCRN108 could promote such inhibition activity of NbCAMTA2. Our results elucidated the multiple roles of PsCRN108 in the suppression of plant immunity and revealed a new mechanism by which the CRN effector hijacked transcription factors to affect immunity. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Patch-Based Convolutional Encoder: A Deep Learning Algorithm for Spectral Classification Balancing the Local and Global Information.

Molecular vibrational spectroscopies, including infrared absorption and Raman scattering, provide molecular fingerprint information and are powerful tools for qualitative and quantitative analysis. They benefit from the recent development of deep-learning-based algorithms to improve the spectral, spatial, and temporal resolutions. Although a variety of deep-learning-based algorithms, including those to simultaneously extract the global and local spectral features, have been developed for spectral classification, the classification accuracy is still far from satisfactory when the difference becomes very subtle. Here, we developed a lightweight algorithm named patch-based convolutional encoder (PACE), which effectively improved the accuracy of spectral classification by extracting spectral features while balancing local and global information. The local information was captured well by segmenting the spectrum into patches with an appropriate patch size. The global information was extracted by constructing the correlation between different patches with depthwise separable convolutions. In the five open-source spectral data sets, PACE achieved a state-of-the-art performance. The more difficult the classification, the better the performance of PACE, compared with that of residual neural network (ResNet), vision transformer (ViT), and other commonly used deep learning algorithms. PACE helped improve the accuracy to 92.1% in Raman identification of pathogen-derived extracellular vesicles at different physiological states, which is much better than those of ResNet (85.1%) and ViT (86.0%). In general, the precise recognition and extraction of subtle differences offered by PACE are expected to facilitate vibrational spectroscopy to be a powerful tool toward revealing the relevant chemical reaction mechanisms in surface science or realizing the early diagnosis in life science.

Signal2signal: Pushing the Spatiotemporal Resolution to the Limit by Single Chemical Hyperspectral Imaging.

There is growing interest in developing a high-performance self-supervised denoising algorithm for real-time chemical hyperspectral imaging. With a good understanding of the working function of the zero-shot Noise2Noise-based denoising algorithm, we developed a self-supervised Signal2Signal (S2S) algorithm for real-time denoising with a single chemical hyperspectral image. Owing to the accurate distinction and capture of the weak signal from the random fluctuating noise, S2S displays excellent denoising performance, even for the hyperspectral image with a spectral signal-to-noise ratio (SNR) as low as 1.12. Under this condition, both the image clarity and the spatial resolution could be significantly improved and present an almost identical pattern with a spectral SNR of 7.87. The feasibility of real-time denoising during imaging was well demonstrated, and S2S was applied to monitor the photoinduced exfoliation of transition metal dichalcogenide, which is hard to accomplish by confocal Raman spectroscopy. In general, the real-time denoising capability of S2S offers an easy way toward in situ/in vivo/operando research with much improved spatial and temporal resolution. S2S is open-source at https://github.com/3331822w/Signal2signal and will be accessible online at https://ramancloud.xmu.edu.cn/tutorial.

Deep Learning-Assisted Spectrum-Structure Correlation: State-of-the-Art and Perspectives.

Spectrum-structure correlation is playing an increasingly crucial role in spectral analysis and has undergone significant development in recent decades. With the advancement of spectrometers, the high-throughput detection triggers the explosive growth of spectral data, and the research extension from small molecules to biomolecules accompanies massive chemical space. Facing the evolving landscape of spectrum-structure correlation, conventional chemometrics becomes ill-equipped, and deep learning assisted chemometrics rapidly emerges as a flourishing approach with superior ability of extracting latent features and making precise predictions. In this review, the molecular and spectral representations and fundamental knowledge of deep learning are first introduced. We then summarize the development of how deep learning assist to establish the correlation between spectrum and molecular structure in the recent 5 years, by empowering spectral prediction (i.e., forward structure-spectrum correlation) and further enabling library matching and de novo molecular generation (i.e., inverse spectrum-structure correlation). Finally, we highlight the most important open issues persisted with corresponding potential solutions. With the fast development of deep learning, it is expected to see ultimate solution of establishing spectrum-structure correlation soon, which would trigger substantial development of various disciplines.

Atovaquone enhances antitumor efficacy of TCR-T therapy by augmentation of ROS-induced ferroptosis in hepatocellular carcinoma.

T-cell receptor (TCR) engineered T-cell therapy has recently emerged as a promising adoptive immunotherapy approach for tumor treatment, yet hindered by tumor immune evasion resulting in poor therapeutic efficacy. The introduction of ferroptosis-targeted inducers offers a potential solution, as they empower T cells to induce ferroptosis and exert influence over the tumor microenvironment. Atovaquone (ATO) stands as a prospective pharmaceutical candidate with the potential to target ferroptosis, effectively provoking an excessive generation and accumulation of reactive oxygen species (ROS). In this study, we evaluated the effectiveness of a combination therapy comprising ATO and TCR-T cells against hepatocellular carcinoma (HCC), both in vitro and in vivo. The results of lactate dehydrogenase and cytokine assays demonstrated that ATO enhanced cytotoxicity mediated by AFP-specific TCR-T cells and promoted the release of IFN-γ in vitro. Additionally, in an established HCC xenograft mouse model, the combined therapy with low-dose ATO and TCR-T cells exhibited heightened efficacy in suppressing tumor growth, with no apparent adverse effects, comparable to the results achieved through monotherapy. The RNA-seq data unveiled a significant activation of the ferroptosis-related pathway in the combination therapy group in comparison to the TCR-T cells group. Mechanistically, the synergy between ATO and TCR-T cells augmented the release of IFN-γ by TCR-T cells, while concurrently elevating the intracellular and mitochondrial levels of ROS, expanding the labile iron pool, and impairing the integrity of the mitochondrial membrane in HepG2 cells. This multifaceted interaction culminated in the potentiation of ferroptosis within the tumor, primarily induced by an excess of ROS. In summary, the co-administration of ATO and TCR-T cells in HCC exhibited heightened vulnerability to ferroptosis. This heightened susceptibility led to the inhibition of tumor growth and the stimulation of an anti-tumor immune response. These findings suggest that repurposing atovaquone for adoptive cell therapy combination therapy holds the potential to enhance treatment outcomes in HCC.

The Phytophthora sojae effector PsFYVE1 modulates immunity-related gene expression by targeting host RZ-1A protein.

Oomycete pathogens secrete numerous effectors to manipulate plant immunity and promote infection. However, relatively few effector types have been well characterized. In this study, members of an FYVE domain-containing protein family that are highly expanded in oomycetes were systematically identified, and one secreted protein, PsFYVE1, was selected for further study. PsFYVE1 enhanced Phytophthora capsici infection in Nicotiana benthamiana and was necessary for Phytophthora sojae virulence. The FYVE domain of PsFYVE1 had PI3P-binding activity that depended on four conserved amino acid residues. Furthermore, PsFYVE1 targeted RNA-binding proteins RZ-1A/1B/1C in N. benthamiana and soybean (Glycine max), and silencing of NbRZ-1A/1B/1C genes attenuated plant immunity. NbRZ-1A was associated with the spliceosome complex that included three important components, glycine-rich RNA-binding protein 7 (NbGRP7), glycine-rich RNA-binding protein 8 (NbGRP8), and a specific component of the U1 small nuclear ribonucleoprotein complex (NbU1-70K). Notably, PsFYVE1 disrupted NbRZ-1A-NbGRP7 interaction. RNA-seq and subsequent experimental analysis demonstrated that PsFYVE1 and NbRZ-1A not only modulated pre-mRNA alternative splicing (AS) of the necrotic spotted lesions 1 (NbNSL1) gene, but also co-regulated transcription of hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyl transferase (NbHCT), ethylene insensitive 2 (NbEIN2), and sucrose synthase 4 (NbSUS4) genes, which participate in plant immunity. Collectively, these findings indicate that the FYVE domain-containing protein family includes potential uncharacterized effector types and also highlight that plant pathogen effectors can regulate plant immunity-related genes at both AS and transcription levels to promote disease.

Comparative genome-wide analysis of circular RNAs in Brassica napus L.: target-site versus non-target-site resistance to herbicide stress.

Circular RNAs (circRNAs), a class of non-coding RNA molecules, are recognized for their unique functions; however, their responses to herbicide stress in Brassica napus remain unclear. In this study, the role of circRNAs in response to herbicide treatment was investigated in two rapeseed cultivars: MH33, which confers non-target-site resistance (NTSR), and EM28, which exhibits target-site resistance (TSR). The genome-wide circRNA profiles of herbicide-stressed and non-stressed seedlings were analyzed. The findings indicate that NTSR seedlings exhibited a greater abundance of circRNAs, shorter lengths of circRNAs and their parent genes, and more diverse functions of parent genes compared with TSR seedlings. Compared to normal-growth plants, the herbicide-stressed group exhibited similar trends in the number of circRNAs, functions of parent genes, and differentially expressed circRNAs as observed in NTSR seedlings. In addition, a greater number of circRNAs that function as competing microRNA (miRNA) sponges were identified in the herbicide stress and NTSR groups compared to the normal-growth and TSR groups, respectively. The differentially expressed circRNAs were validated by qPCR. The differntially expressed circRNA-miRNA networks were predicted, and the mRNAs targeted by these miRNAs were annotated. Our results suggest that circRNAs play a crucial role in responding to herbicide stress, exhibiting distinct responses between NTSR and TSR in rapeseed. These findings offer valuable insights into the mechanisms underlying herbicide resistance in rapeseed.

Atg5 deficiency in macrophages protects against kidney fibrosis via the CCR6-CCL20 axis.

BACKGROUND: Autophagy is a lysosome-dependent degradation pathway that regulates macrophage activation, differentiation, and polarization. Autophagy related 5 (Atg5) is a key protein involved in phagocytic membrane elongation in autophagic vesicles that forms a complex with Atg12 and Atg16L1. Alterations in Atg5 are related to both acute and chronic kidney diseases in experimental models. However, the role of macrophage-expressed Atg5 in acute kidney injury remains unclear. METHODS: Using a myeloid cell-specific Atg5 knockout (MΦ atg5-/-) mouse, we established renal ischemia/reperfusion and unilateral ureteral obstruction models to evaluate the role of macrophage Atg5 in renal macrophage migration and fibrosis. RESULTS: Based on changes in the serum urea nitrogen and creatinine levels, Atg5 deletion had a minimal effect on renal function in the early stages after mild injury; however, MΦ atg5-/- mice had reduced renal fibrosis and reduced macrophage recruitment after 4 weeks of ischemia/reperfusion injury and 2 weeks of unilateral ureteral obstruction injury. Atg5 deficiency impaired the CCL20-CCR6 axis after severe ischemic kidneys. Chemotactic responses of bone marrow-derived monocytes (BMDMs) from MΦ atg5-/- mice to CCL20 were significantly attenuated compared with those of wild-type BMDMs, and this might be caused by the inhibition of PI3K, AKT, and ERK1/2 activation. CONCLUSIONS: Our data indicate that Atg5 deficiency decreased macrophage migration by impairing the CCL20-CCR6 axis and inhibited M2 polarization, thereby improving kidney fibrosis.

Phytic acid/tannic acid reinforced hydrogels with ultra-high strength for human motion monitoring and arrays.

Conductive hydrogels have been widely researched for their potential applications in soft electronic devices. Creating environmentally friendly and multifunctional high-strength hydrogels for high-performance devices remains a significant challenge. This study employs the biodegradable material polyvinyl alcohol (PVA) as the primary component, with phytic acid (PA) and tannic acid (TA) as reinforcing phases, to create a multifunctional, high-strength "green" hydrogel. Through the multiple complexations of two bio-enhancing phases with the PVA main chain, this hydrogel attains ultra-high tensile strength (9.341 MPa), substantial toughness (4.262 MJ m-3), and extensive fracture strain (> 1000%), making it a representative with both mechanical performance and antibacterial capabilities. Additionally, it exhibits a low strain sensing limit (0.5%) and excellent durability (500 cycles under 50% strain). This work introduces a novel strategy of combining biodegradable materials with biomass to fabricate multifunctional hydrogels suitable for human motion monitoring and 2D pressure distribution.

Interpregnancy interval, air pollution, and the risk of low birth weight: a retrospective study in China.

BACKGROUND: Both interpregnancy intervals (IPI) and environmental factors might contribute to low birth weight (LBW). However, the extent to which air pollution influences the effect of IPIs on LBW remains unclear. We aimed to investigate whether IPI and air pollution jointly affect LBW. METHODS: A retrospective cohort study was designed in this study. The data of birth records was collected from the Jiangsu Maternal Child Information System, covering January 2020 to June 2021 in Nantong city, China. IPI was defined as the duration between the delivery date for last live birth and date of LMP for the subsequent birth. The maternal exposure to ambient air pollutants during pregnancy-including particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 µm (PM2.5), PM10, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO)-was estimated using a hybrid kriging-LUR-RF model. A novel air pollution score was proposed, assessing combined exposure to five pollutants (excluding CO) by summing their concentrations, weighted by LBW regression coefficients. Multivariate logistic regression models were used to estimate the effects of IPI, air pollution and their interactions on LBW. Relative excess risk due to interaction (RERI), attributable proportion of interaction (AP) and synergy index (S) were utilized to assess the additive interaction. RESULTS: Among 10, 512 singleton live births, the LBW rate was 3.7%. The IPI-LBW risk curve exhibited an L-shaped pattern. The odds ratios (ORs) for LBW for each interquartile range increase in PM2.5, PM10, O3 and the air pollution score were 1.16 (95% CI: 1.01-1.32), 1.30 (1.06-1.59), 1.22 (1.06-1.41), and 1.32 (1.10-1.60) during the entire pregnancy, respectively. An additive interaction between IPI and PM2.5 was noted during the first trimester. Compared to records with normal IPI and low PM2.5 exposure, those with short IPI and high PM2.5 exposure had the highest risk of LBW (relative risk = 3.53, 95% CI: 1.85-6.49, first trimester). CONCLUSION: The study demonstrates a synergistic effect of interpregnancy interval and air pollution on LBW, indicating that rational birth spacing and air pollution control can jointly improve LBW outcomes.

Effect of pretreatment with a small dose of esketamine on sufentanil-induced cough during anesthesia induction: a randomized controlled trial.

BACKGROUND: Sufentanil-induced cough is common during the induction of anesthesia. The objective of this study was to determine whether pretreatment with a small dose of esketamine is effective in treating sufentanil-induced cough. METHODS: 220 patients were screened, and 200 patients who had scheduled elective surgery and were between 18 and 70 years old were randomly divided into two groups. Before sufentanil was administered, esketamine group (group K) was injected with 0.15 mg/kg esketamine at 5 s, and control group (group C) was administered with the same volume. Within 1 min after sufentanil(0.4ug/kg) injection during induction, cough incidence and severity were evaluated. After sufentanil was injected, we recorded its hemodynamic changes and side effects. RESULTS: In the esketamine group (group K) and control group (group C), there was an incidence of cough of 5 and 34%, respectively. The esketamine group (group K) had a significantly lower incidence and severity of cough compared to the control group (group C) immediately after sufentanil injection (P < 0.05). MAP and HR did not differ significantly between the two groups during three different times of general anesthesia induction (P > 0.05). CONCLUSION: In our study, we found that sufentanil-induced cough was significantly reduced by pretreatment with 0.15 mg/kg esketamine, but with no significant changes in the hemodynamic status. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR2200063821, registered date: 17/09/2022), http://www.chictr.org.cn.

Anti-angiogenesis agents plus chemoradiotherapy for locally advanced nasopharyngeal cancer: a systematic review and meta-analysis.

PURPOSE: To evaluate literature evidences about the efficacy and safety of anti-angiogenesis agents plus chemoradiotherapy versus chemoradiotherapy in the treatment of locally advanced nasopharyngeal carcinoma. METHODS: The relevant literature was systematically searched from the date of establishment to April 2023 in PubMed, Embase, Web of Science, The Cochrane Library, Chinese National Knowledge Infrastructure, Chinese Biological Medicine, Wanfang and VIP database. Search terms included: Nasopharyngeal Neoplasms, Angiogenesis inhibitors, Endostar, Anlotinib, Apatinib, Bevacizumab, Sunitinib, Pazopanib, Chemoradiotherapy. The literature was strictly screened according to the inclusion and exclusion criteria, and 8 eligible studies were finally included in our meta-analysis (4 randomized controlled trials and 4 retrospective studies). RESULTS: A total of 642 patients were included, with 316 in the anti-angiogenesis agents plus chemoradiotherapy group and 326 in the chemoradiotherapy group. The results of our meta-analysis showed that compared with chemoradiotherapy group, the complete response rate (RR = 1.35, 95% CI 1.05-1.74, P = 0.02), objective response rate (RR = 1.26, 95% CI 1.12-1.43, P = 0.0002) in the anti-angiogenesis agents plus chemoradiotherapy group were significantly improved. In terms of safety, there was a higher incidence of cardiac arrhythmia (RR = 3.63, 95% CI 1.16-11.37, P = 0.03) and hypertension (RR = 1.85, 95% CI 1.04-3.27, P = 0.004) in the anti-angiogenesis agents plus chemoradiotherapy group, while no statistically significant differences were reported in other adverse reactions (all P > 0.05). CONCLUSION: Compared with chemoradiotherapy, anti-angiogenesis agents plus chemoradiotherapy could bring more benefits in terms of short-term efficacy, particularly by notably improving both complete response rate and objective response rate, and overall adverse reactions were acceptable. Anti-angiogenesis agents plus chemoradiotherapy may provide a promising direction for the treatment of locally advanced nasopharyngeal carcinoma. SYSTEMATIC REVIEW REGISTRATION: https://inplasy.com/inplasy-2023-8-0076/ , registration number INPLASY202380076.

Ultrasound-electrochemistry assisted liquid-phase co-exfoliation of phosphorene decorated by Au-Ag bimetallic nanoparticles as nanozyme for smartphone-based portable sensing of 4-nitrophenol.

The stability of black phosphorene (BP) and its preparation and modification for developing and applying devices have become a hot topic in the interdisciplinary field. We propose ultrasound-electrochemistry co-assisted liquid-phase exfoliation as an eco-friendly one-step method to prepare gold-silver bimetallic nanoparticles (Au-AgNPs)-decorated BP nanozyme for smartphone-based portable sensing of 4-nitrophenol (4-NP) in different water sources. The structure, morphology, composition, and properties of Au-AgNPs-BP nanozyme are characterized by multiple instrumental analyses. Bimetallic salts are induced to efficiently occupy oxidative sites of BP to form highly stable Au-AgNPs-BP nanozyme and guarantee the integrity of the lamellar BP. The electrochemistry shortens the exfoliation time of the BP nanosheet and contributes to the loading efficiency of bimetallic nanoparticles on the BP nanosheet. Au-AgNPs-BP-modified screen-printed carbon electrode coupled with palm-sized smartphone-controlled wireless electrochemical analyzer as a portable wireless intelligent sensing platform was applied to the determination of 4-NP in a linear range of 0.6-10 µM with a limit of detection of 63 nM. It enables on-site determination of 4-NP content in lake water, river water, and irrigation ditch water. This work will provide a reference for an eco-friendly one-step preparation of bimetallic nanoparticle-decorated graphene-like materials as nanozymes and their smartphone-based portable sensing application outdoors.

Unraveling the Molecular Basis of Color Variation in Dioscorea alata Tubers: Integrated Transcriptome and Metabolomics Analysis.

Dioscorea alata L. (Dioscoreaceae) is a widely cultivated tuber crop with variations in tuber color, offering potential value as health-promoting foods. This study focused on the comparison of D. alata tubers possessing two distinct colors, white and purple, to explore the underlying mechanisms of color variation. Flavonoids, a group of polyphenols known to influence plant color and exhibit antioxidant properties, were of particular interest. The total phenol and total flavonoid analyses revealed that purple tubers (PTs) have a significantly higher content of these metabolites than white tubers (WTs) and a higher antioxidant activity than WTs, suggesting potential health benefits of PT D. alata. The transcriptome analysis identified 108 differentially expressed genes associated with the flavonoid synthesis pathway, with 57 genes up-regulated in PTs, including CHS, CHI, DFR, FLS, F3H, F3'5'H, LAR, ANS, and ANR. The metabolomics analysis demonstrated that 424 metabolites, including 104 flavonoids and 8 tannins, accumulated differentially in PTs and WTs. Notably, five of the top ten up-regulated metabolites were flavonoids, including 6-hydroxykaempferol-7-O-glucoside, pinocembrin-7-O-(6″-O-malonyl)glucoside, 6-hydroxykaempferol-3,7,6-O-triglycoside, 6-hydroxykaempferol-7-O-triglycoside, and cyanidin-3-O-(6″-O-feruloyl)sophoroside-5-O-glucoside, with the latter being a precursor to anthocyanin synthesis. Integrating transcriptome and metabolomics data revealed that the 57 genes regulated 20 metabolites within the flavonoid synthesis pathway, potentially influencing the tubers' color variation. The high polyphenol content and antioxidant activity of PTs indicate their suitability as nutritious and health-promoting food sources. Taken together, the findings of this study provide insights into the molecular basis of tuber color variation in D. alata and underscore the potential applications of purple tubers in the food industry and human health promotion. The findings contribute to the understanding of flavonoid biosynthesis and pigment accumulation in D. alata tubers, opening avenues for future research on enhancing the nutritional quality of D. alata cultivars.

Recurrent spinal subdural hematoma following percutaneous kyphoplasty: A unique case report.

Spinal intradural (subdural and subarachnoid) hematoma following percutaneous kyphoplasty is an extremely rare complication. In this report, we described a case of 2 episodes of subarachnoid hemorrhage with delayed paralysis after kyphoplasty. A 73-year-old man underwent percutaneous kyphoplasty in our hospital an osteoporotic vertebral fracture at the T12 level. On the 55 h after kyphoplasty for T12 osteoporotic vertebral fracture, he developed paralysis of the lower limbs. An emergency posterior decompression from T8 to L2 was performed. And the subarachnoid hematomas were removed. Postoperatively, the neurological symptoms improved rapidly. However, 2 weeks after the operation, the patient experienced a setback with severe neurological decline (paraplegia with sensory and autonomic dysfunction). An emergency posterior decompression from T5 to L2 was performed. The subarachnoid hematomas were removed. This case reflects the cause and progression of spinal subdural hematoma. Previous literature has debated the best treatment approach for spinal subarachnoid hemorrhage, but the prognosis of patients is heavily dependent on precise symptom evaluation and localization.

Aqueous Developable and CO2-Sourced Chemical Amplification Photoresist with High Performance.

Seeking high-performance photoresists is an important item for semiconductor industry due to the continuous miniaturization and intelligentization of integrated circuits. Polymer resin containing carbonate group has many desirable properties, such as high transmittance, acid sensitivity and chemical formulation, thus serving as promising photoresist material. In this work, a series of aqueous developable CO2-sourced polycarbonates (CO2-PCs) were produced via alternating copolymerization of CO2 and epoxides bearing acid-cleavable cyclic acetal groups in the presence of tetranuclear organoborane catalyst. The produced CO2-PCs were investigated as chemical amplification resists in deep ultraviolet (DUV) lithography. Under the catalysis of photogenerated acid, the acetal (ketal) groups in CO2-PC were hydrolysed into two equivalents of hydroxyl groups, which change the exposed area from hydrophobicity to hydrophilicity, thus enabling the exposed area to be developed with water. Through normalized remaining thickness analysis, the optimal CO2-derived resist achieved a remarkable sensitivity of 1.9 mJ/cm2, a contrast of 7.9, a favorable resolution (750 nm, half pitch), and a good etch resistance (38 % higher than poly(tert-butyl acrylate)). Such performances outperform commercial KrF and ArF chemical amplification resists (i.e., polyhydroxystyrene-derived and polymethacrylate-based resists), which endows broad application prospects in the field of DUV (KrF and ArF) and extreme ultraviolet (EUV) lithography for nanomanufacturing.

1D Gradient-Weighted Class Activation Mapping, Visualizing Decision Process of Convolutional Neural Network-Based Models in Spectroscopy Analysis.

Being characterized by the self-adaption and high accuracy, the deep learning-based models have been widely applied in the 1D spectroscopy-related field. However, the "black-box" operation and "end-to-end" working style of the deep learning normally bring the low interpretability, where a reliable visualization is highly demanded. Although there are some well-developed visualization methods, such as Class Activation Mapping (CAM) and Gradient-weighted Class Activation Mapping (Grad-CAM), for the 2D image data, they cannot correctly reflect the weights of the model when being applied to the 1D spectral data, where the importance of position information is not considered. Here, aiming at the visualization of Convolutional Neural Network-based models toward the qualitative and quantitative analysis of 1D spectroscopy, we developed a novel visualization algorithm (1D Grad-CAM) to more accurately display the decision-making process of the CNN-based models. Different from the classical Grad-CAM, with the removal of the gradient averaging (GAP) and the ReLU operations, a significantly improved correlation between the gradient and the spectral location and a more comprehensive spectral feature capture were realized for 1D Grad-CAM. Furthermore, the introduction of difference (purity or linearity) and feature contribute in the CNN output in 1D Grad-CAM achieved a reliable evaluation of the qualitative accuracy and quantitative precision of CNN-based models. Facing the qualitative and adulteration quantitative analysis of vegetable oils by the combination of Raman spectroscopy and ResNet, the visualization by 1D Grad-CAM well reflected the origin of the high accuracy and precision brought by ResNet. In general, 1D Grad-CAM provides a clear vision about the judgment criterion of CNN and paves the way for CNN to a broad application in the field of 1D spectroscopy.

Strategies and rules for tuning TCR-derived therapy.

Manipulation of T cells has revolutionized cancer immunotherapy. Notably, the use of T cells carrying engineered T cell receptors (TCR-T) offers a favourable therapeutic pathway, particularly in the treatment of solid tumours. However, major challenges such as limited clinical response efficacy, off-target effects and tumour immunosuppressive microenvironment have hindered the clinical translation of this approach. In this review, we mainly want to guide TCR-T investigators on several major issues they face in the treatment of solid tumours after obtaining specific TCR sequences: (1) whether we have to undergo affinity maturation or not, and what parameter we should use as a criterion for being more effective. (2) What modifications can be added to counteract the tumour inhibitory microenvironment to make our specific T cells to be more effective and what is the safety profile of such modifications? (3) What are the new forms and possibilities for TCR-T cell therapy in the future?

Comparative proteomic and physiological analyses reveal tribenuron-methyl phytotoxicity and nontarget-site resistance mechanisms in Brassica napus.

The application of herbicides is the most effective strategy for weed control and the development of herbicide-resistant crops will facilitate the weed management. The acetolactate synthase-inhibiting herbicide, tribenuron-methyl (TBM), is broadly used for weed control. However, its application in rapeseed field is restricted since rapeseed is sensitive to TBM. Herein, an integrated study of cytological, physiological and proteomic analysis of the TBM-resistant rapeseed mutant M342 and its wild-type (WT) plants was conducted. After TBM spraying, M342 showed improved tolerance to TBM, and proteins implicated in non-target-site resistance (NTSR) to herbicides had a significantly higher level in M342 as compared with the WT. Differentially accumulated proteins (DAPs) between these two genotypes were enriched in glutathione metabolism and oxidoreduction coenzyme metabolic process, which protected the mutant from oxidative stress triggered by TBM. Important DAPs related to stress or defence response were up-accumulated in M342 regardless of the TBM treatment, which might serve as the constitutive part of NTSR to TBM. These results provide new clues for further exploration of the NTSR mechanism in plants and establish a theoretical basis for the development of herbicide-resistant crops.