A simplified reliability-based design method for multiple design variables considering different limit states.

A generalized reliability model comprising the objective, constraint, and judgment functions is established for the reliability index approach (RIA), taking parameters' properties of engineering practice and negative reliability index into consideration. Based on this, the reliability-based design (RBD) problem with multiple design variables is translated into the solution to the nonlinear equations, and a simplified method consisting of a simple variant of the Newton iteration method and the finite difference method (FDM) is proposed. Numerical examples are presented to verify the efficiency of the proposed reliability approach and to determine the incremental step size for FDM. RBD of a simply supported beam is illustrated and the variabilities of design variables are investigated considering the uncertainties in the manufacturing process and practical operations. Results reveal that the variations of the design variables should not be ignored. Moreover, analysis results show that the design value might not intuitively increase with the increase of its coefficient of variation (CoV), and it might not increase with the increasing reliability requirement for problems involving multiple variables. The reasons for this phenomenon are very complicated, and it is a systematic problem. One should be aware of this phenomenon, and specific analysis is required for specific problems.

Removal mechanism of Pb(ii) from soil by biochar-supported nanoscale zero-valent iron composite materials.

As an adsorbent, biochar has a highly porous structure and strong adsorption capacity, and can effectively purify the environment. In response to the increasingly serious problem of heavy metal pollution in water, this study used nano zero valent iron and rice husk biochar to prepare a new type of magnetic sheet-like biochar loaded nano zero valent iron (BC-nZVI) composite material through rheological phase reaction, showing remarkable advantages such as low cost, easy preparation, and superior environmental remediation effect. The physical and chemical properties and structure of the material were extensively characterized using various methods such as HRTEM, XPS, FESEM, EDS, XRD, FTIR, and RAMAN. Concurrently, batch experiments were undertaken to assess the removal efficiency of Pb(ii) by BC-nZVI, with investigations into the influence of pH value, temperature, soil water ratio, and initial concentration of heavy metal ion solution on its removal efficiency. The results indicate that the removal of Pb(ii) by BC-nZVI reaches an equilibrium state after around 120 minutes. Under the conditions of pH 6, temperature 20 °C, soil water ratio 1 : 5, and BC-nZVI dosage of 1 g L-1, BC-nZVI can reduce the Pb(ii) content in wastewater with an initial concentration of 30 mg L-1 to trace levels, and the treatment time is about 120 minutes. The analysis of adsorption kinetics and isotherms indicates that the adsorption process of Pb(ii) by BC-nZVI adheres to the quasi-second-order kinetic model and Langmuir model, suggesting a chemical adsorption process. Thermodynamic findings reveal that the adsorption of Pb(ii) by BC-nZVI is spontaneous. Furthermore, BC-nZVI primarily accumulates Pb(ii) through adsorption co-precipitation. BC-nZVI serves as an eco-friendly, cost-effective, and highly efficient adsorbent, showing promising capabilities in mitigating Pb(ii) heavy metal pollution. Its recoverability and reusability facilitated by an external magnetic field make it advantageous for remediating and treating lead-contaminated sites.

Aerodynamic Simulation of Small Airway Resistance: A New Imaging Biomarker for Chronic Obstructive Pulmonary Disease.

Purpose: To develop a novel method for calculating small airway resistance using computational fluid dynamics (CFD) based on CT data and evaluate its value to identify COPD. Patients and Methods: 24 subjects who underwent chest CT scans and pulmonary function tests between August 2020 and December 2020 were enrolled retrospectively. Subjects were divided into three groups: normal (10), high-risk (6), and COPD (8). The airway from the trachea down to the sixth generation of bronchioles was reconstructed by a 3D slicer. The small airway resistance (RSA) and RSA as a percentage of total airway resistance (RSA%) were calculated by CFD combined with airway resistance and FEV1 measured by pulmonary function test. A correlation analysis was conducted between RSA and pulmonary function parameters, including FEV1/FVC, FEV1% predicted, MEF50% predicted, MEF75% predicted and MMEF75/25% predicted. Results: The RSA and RSA% were significantly different among the three groups (p<0.05) and related to FEV1/FVC (r = -0.70, p < 0.001; r = -0.67, p < 0.001), FEV1% predicted (r = -0.60, p = 0.002; r = -0.57, p = 0.004), MEF50% predicted (r = -0.64, p = 0.001; r = -0.64, p = 0.001), MEF75% predicted (r = -0.71, p < 0.001; r = -0.60, p = 0.002) and MMEF 75/25% predicted (r = -0.64, p = 0.001; r = -0.64, p = 0.001). Conclusion: Airway CFD is a valuable method for estimating the small airway resistance, where the derived RSA will aid in the early diagnosis of COPD.

New Insights into Photo-Fenton Chemistry: The Overlooked Role of Excited IronIII Species.

Direct photoreduction of FeIII is a widely recognized route for accelerating FeIII/FeII cycle in photo-Fenton chemistry. However, most of the wavelengths covering the full spectral range are insufficient to supply enough photon energy for the direct reduction process. Herein, the hitherto neglected mechanism of FeIII reduction that the FeIII indirect reduction pathway initiated by light energy-dependent reactivity variation and reactive excited state (ES) was explored. Evolution of excited-state FeIII species (*FeIII) resulting from metal-centered charge excitation (MCCE) of FeIII is experimentally verified using pulsed laser femtosecond transient absorption spectroscopy with UV-vis detection and theoretically verified by quantum chemical calculation. Intense photoinduced intravalence charge transition was observed at λ = 380 and 466 nm, revealing quartet 4MCCE and doublet 2MCCE and their exponential processes. Light energy-dependent variation of *FeIII reactivity was kinetically certified by fitting the apparent rate constant of the radical-chain sequence of photo-Fenton reactions. Covalency is found to compensate for the intravalence charge separation following photoexcitation of the metal center in the MCCE state of Fenton photosensitizer. The *FeIII is established as a model, demonstrating the intravalence hole delocalization in the ES can be leveraged for photo-Fenton reaction or other photocatalytic schemes based on electron transfer chemistry.

Quantitative profiling of m6A at single base resolution across the life cycle of rice and Arabidopsis.

N6-methyladenosine (m6A) plays critical roles in regulating mRNA metabolism. However, comprehensive m6A methylomes in different plant tissues with single-base precision have yet to be reported. Here, we present transcriptome-wide m6A maps at single-base resolution in different tissues of rice and Arabidopsis using m6A-SAC-seq. Our analysis uncovers a total of 205,691 m6A sites distributed across 22,574 genes in rice, and 188,282 m6A sites across 19,984 genes in Arabidopsis. The evolutionarily conserved m6A sites in rice and Arabidopsis ortholog gene pairs are involved in controlling tissue development, photosynthesis and stress response. We observe an overall mRNA stabilization effect by 3' UTR m6A sites in certain plant tissues. Like in mammals, a positive correlation between the m6A level and the length of internal exons is also observed in plant mRNA, except for the last exon. Our data suggest an active m6A deposition process occurring near the stop codon in plant mRNA. In addition, the MTA-installed plant mRNA m6A sites correlate with both translation promotion and translation suppression, depicting a more complicated regulatory picture. Our results therefore provide in-depth resources for relating single-base resolution m6A sites with functions in plants and uncover a suppression-activation model controlling m6A biogenesis across species.

Rapid-response near-infrared fluorescence probe for colorimetric detection of HClO and its applications in environmental monitoring and biological imaging.

As a crucial endogenous reactive oxygen species, hypochlorous acid (HClO) plays an indispensable role in numerous physiological and pathological processes. Additionally, it serves as a biomarker closely associated with inflammation and liver injury. The utilization of near-infrared fluorescence probes has surged in recent years for live biological imaging, owing to their minimal tissue damage and potent tissue penetration capabilities. In this work, a novel near-infrared fluorescence probe MB-HPD was synthesized to sensitively detect HClO. Probe MB-HPD exhibits remarkable selectivity, high sensitivity (14.3 nM), and rapid response towards HClO (20 s). Probe MB-HPD has demonstrated successful application in the imaging of HClO within cells and zebrafish. Remarkably, it has proven to be effective for detecting HClO within environmental samples, as well as imaging HClO in mice models of arthritis and APAP-induced liver injury. These findings indicate the broad applicability of probe MB-HPD, offering a promising avenue for designing highly selective near-infrared fluorescence probes suitable for real-time HClO monitoring.

Anti-BCMA-engineered Exosomes for Bortezomib Targeted Delivery in Multiple Myeloma.

Exosomes have emerged as promising vehicles for delivering therapeutic cargoes to specific cells or tissues, owing to their superior biocompatibility, reduced immunogenicity, and enhanced targeting capabilities compared to conventional drug delivery systems. In this study, we developed a delivery platform utilizing exosomes derived from monocytes, specifically designed for targeted delivery of Bortezomib (Btz) to multiple myeloma (MM) cells. Our approach involved the genetic modification of monocytes to express antibodies targeting B cell maturation antigen (anti-BCMA), as BCMA selectively expresses on myeloma cells. This modified anti-BCMA was then efficiently incorporated into the monocyte-derived exosomes. These adapted exosomes effectively encapsulated Bortezomib, leading to enhanced drug accessibility within MM cells and sustained intracellular accumulation over an extended period. Remarkably, our results demonstrated that anti-BCMA-Exo-Btz outperformed free Btz in vitro, exhibiting a more potent myeloma-suppressive effect. In orthotopic MM xenograft models, anti-BCMA-Exo-Btz exhibited a significant anti-tumor effect compared to free Btz. Furthermore, it demonstrated remarkable specificity in targeting Bortezomib to myeloma cells in vivo. Importantly, we observed no significant histological damage in mice treated with anti-BCMA-Exo-Btz and a slight effect on PBMCs. Additionally, our study highlighted the multifunctional potential of monocyte-exosomes, which induced cell apoptosis, mediated immune responses, and enhanced the osteogenic potential of mesenchymal stromal cells. In conclusion, our study suggests that exosomes modified with targeting ligands hold therapeutic promise for delivering Bortezomib to myelomas, offering substantial potential for clinical applications.

LABS: linear amplification-based bisulfite sequencing for ultrasensitive cancer detection from cell-free DNA.

Methylation-based liquid biopsies show promises in detecting cancer using circulating cell-free DNA; however, current limitations impede clinical application. Most assays necessitate substantial DNA inputs, posing challenges. Additionally, underrepresented tumor DNA fragments may go undetected during exponential amplification steps of traditional sequencing methods. Here, we report linear amplification-based bisulfite sequencing (LABS), enabling linear amplification of bisulfite-treated DNA fragments in a genome-wide, unbiased fashion, detecting cancer abnormalities with sub-nanogram inputs. Applying LABS to 100 patient samples revealed cancer-specific patterns, copy number alterations, and enhanced cancer detection accuracy by identifying tissue-of-origin and immune cell composition.

Targeting the dendritic cell-secreted immunoregulatory cytokine CCL22 alleviates radioresistance.

PURPOSE: Radiation-mediated immune suppression limits efficacy and is a barrier in cancer therapy. Radiation induces negative regulators of tumor immunity including regulatory T cells (Treg). Mechanisms underlying Treg infiltration after radiotherapy (RT) are poorly defined. Given that dendritic cells (cDC) maintain Treg we sought to identify and target cDC signaling to block Treg infiltration after radiation. EXPERIMENTAL DESIGN: Transcriptomics and high dimensional flow cytometry revealed changes in murine tumor cDC that not only mediate Treg infiltration after RT, but associate with worse survival in human cancer datasets. Antibodies perturbing a cDC-CCL22-Treg axis were tested in syngeneic murine tumors. A prototype interferon-anti-epidermal growth factor receptor fusion protein (αEGFR-IFNα) was examined to block Treg infiltration and promote a CD8+ T cell response after RT. RESULTS: Radiation expands a population of mature cDC1 enriched in immunoregulatory markers that mediates Treg infiltration via the Treg-recruiting chemokine CCL22. Blocking CCL22 or Treg depletion both enhanced RT efficacy. αEGFR-IFNα blocked cDC1 CCL22 production while simultaneously inducing an antitumor CD8+ T cell response to enhance RT efficacy in multiple EGFR-expressing murine tumor models, including following systemic administration. CONCLUSIONS: We identify a previously unappreciated cDC mechanism mediating Treg tumor infiltration after RT. Our findings suggest blocking the cDC1-CCL22-Treg axis augments RT efficacy. αEGFR-IFNα added to RT provided robust antitumor responses better than systemic free interferon administration, and may overcome clinical limitations to interferon therapy. Our findings highlight the complex behavior of cDC after RT and provide novel therapeutic strategies for overcoming RT-driven immunosuppression to improve RT efficacy.

The tumor-intrinsic role of the m6A reader YTHDF2 in regulating immune evasion.

Tumors evade attacks from the immune system through various mechanisms. Here, we identify a component of tumor immune evasion mediated by YTH domain-containing family protein 2 (YTHDF2), a reader protein that usually destabilizes m6A-modified mRNA. Loss of tumoral YTHDF2 inhibits tumor growth and prolongs survival in immunocompetent tumor models. Mechanistically, tumoral YTHDF2 deficiency promotes the recruitment of macrophages via CX3CL1 and enhances mitochondrial respiration of CD8+ T cells by impairing tumor glycolysis metabolism. Tumoral YTHDF2 deficiency promotes inflammatory macrophage polarization and antigen presentation in the presence of IFN-γ. In addition, IFN-γ induces autophagic degradation of tumoral YTHDF2, thereby sensitizing tumor cells to CD8+ T cell-mediated cytotoxicity. Last, we identified a small molecule compound that preferentially induces YTHDF2 degradation, which shows a potent antitumor effect alone but a better effect when combined with anti-PD-L1 or anti-PD-1 antibodies. Collectively, YTHDF2 appears to be a tumor-intrinsic regulator that orchestrates immune evasion, representing a promising target for enhancing cancer immunotherapy.

Anoikis-related gene signatures in colorectal cancer: implications for cell differentiation, immune infiltration, and prognostic prediction.

Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis. However, the key genes and pathways regulating anoikis in CRC are still unclear and require further research. The single cell transcriptome dataset GSE221575 of GEO database was downloaded and applied to cell subpopulation type identification, intercellular communication, pseudo time cell trajectory analysis, and receptor ligand expression analysis of CRC. Meanwhile, the RNA transcriptome dataset of TCGA, the GSE39582, GSE17536, and GSE17537 datasets of GEO were downloaded and merged into one bulk transcriptome dataset. The differentially expressed genes (DEGs) related to anoikis were extracted from these data sets, and key marker genes were obtained after feature selection. A clinical prognosis prediction model was constructed based on the marker genes and the predictive effect was analyzed. Subsequently, gene pathway analysis, immune infiltration analysis, immunosuppressive point analysis, drug sensitivity analysis, and immunotherapy efficacy based on the key marker genes were conducted for the model. In this study, we used single cell datasets to determine the anoikis activity of cells and analyzed the DEGs of cells based on the score to identify the genes involved in anoikis and extracted DEGs related to the disease from the transcriptome dataset. After dimensionality reduction selection, 7 marker genes were obtained, including TIMP1, VEGFA, MYC, MSLN, EPHA2, ABHD2, and CD24. The prognostic risk model scoring system built by these 7 genes, along with patient clinical data (age, tumor stage, grade), were incorporated to create a nomogram, which predicted the 1-, 3-, and 5-years survival of CRC with accuracy of 0.818, 0.821, and 0.824. By using the scoring system, the CRC samples were divided into high/low anoikis-related prognosis risk groups, there are significant differences in immune infiltration, distribution of immune checkpoints, sensitivity to chemotherapy drugs, and efficacy of immunotherapy between these two risk groups. Anoikis genes participate in the differentiation of colorectal cancer tumor cells, promote tumor development, and could predict the prognosis of colorectal cancer.

A 5-hydroxymethylcytosine-based non-invasive model for early detection of colorectal carcinomas and advanced adenomas: the METHOD-2 study.

PURPOSE: Detection of colorectal carcinomas (CRC) at a time when there are more treatment options is associated with better outcomes. This prospective case-control study assessed the 5-hydroxymethylcytosine (5hmC) biomarkers in circulating cell-free DNA (cfDNA) for early detection of CRC and advanced adenomas (AA) Experimental Design: Plasma cfDNA samples from 2,576 study participants from the multi-center METHOD-2 study (NCT03676075) were collected, comprising patients with newly diagnosed CRC (n=1,074), AA (n=356), other solid tumors (n=80), and non-CRC/AA controls (n=1,066), followed by genome-wide 5hmC profiling using the 5hmC-Seal technique and the next-generation sequencing (NGS). A weighted diagnostic model for CRC (stage I-III) and AA was developed using the elastic net regularization in a discovery set and validated in independent samples. RESULTS: Distribution of 5hmC in cfDNA reflected gene regulatory relevance and tissue of origin. Besides being confirmed in internal validation, a 96-gene model achieved an area under the curve (AUC) of 90.7% for distinguishing stage I-III CRC from controls in 321 samples from multiple centers for external validation, regardless of primary location or mutation status. This model also showed cancer-type specificity as well as high capacity for distinguishing AA from controls with an AUC of 78.6%. Functionally, differential 5hmC features associated with CRC and AA demonstrated relevance to CRC biology, including pathways such as calcium and MAPK signaling. CONCLUSIONS: Genome-wide mapping of 5hmC in cfDNA shows the promise as a highly sensitive and specific non-invasive blood test to be integrated in screening programs for improving early detection of CRC and high-risk AA.

The moderating role of work environment in the relationship between proactive personality and personal growth initiative among nurses: a cross-sectional study.

BACKGROUNDS: Personal growth initiative (PGI) is regarded as a meaningful concept with potential value at both the individual and organizational levels, but little is known about the factors that contribute to nurses' PGI. This study aimed to explore how proactive personality and hospital work environment affect PGI of clinical nurses. METHODS: A cross-sectional study was conducted between September and October 2022 among 4414 nurses from 10 tertiary general hospitals in 10 cities in Sichuan, China, using a two-stage sampling method. Self-reported anonymous online questionnaires, such as sociodemographic information survey, personal growth initiative scale II, the 10-item proactive personality scale, and practice environment scale-nursing work index were used to collect data. Multiple hierarchical regression analyses were performed to examine research hypotheses. RESULTS: Among the control variables in this study, nurses' self-perceptions of general health status and professional title positively predicted PGI (ß = 0.462, 95%CI = 0.272-0.653; ß = 1.078, 95%CI = 0.508-1.648). After adding control variables, both proactive personality (ß = 1.143, 95%CI = 1.096-1.190) and work environment (ß = 3.391, 95%CI = 2.904-3.879) positively predicted PGI. The work environment positively moderated the association between proactive personality and PGI (ß = 0.108, 95%CI = 0.025-0.191). These predictors jointly explained 50.3% of the variance in PGI. CONCLUSIONS: Nurses with a greater tendency to have a typical proactive personality have higher levels of personal growth initiative, and this positive effect will be better highlighted in a healthier work environment. Nursing managers should prioritize the employment of people with proactive personality traits, focus on the development and stimulation of proactive personality traits in nurses, and establish a supportive work environment to maximize the personal growth initiative of nurses.

Small-molecule inhibition of the METTL3/METTL14 complex suppresses neuroblastoma tumor growth and promotes differentiation.

The N6-methyladenosine (m6A) RNA modification is an important regulator of gene expression. m6A is deposited by a methyltransferase complex that includes methyltransferase-like 3 (METTL3) and methyltransferase-like 14 (METTL14). High levels of METTL3/METTL14 drive the growth of many types of adult cancer, and METTL3/METTL14 inhibitors are emerging as new anticancer agents. However, little is known about the m6A epitranscriptome or the role of the METTL3/METTL14 complex in neuroblastoma, a common pediatric cancer. Here, we show that METTL3 knockdown or pharmacologic inhibition with the small molecule STM2457 leads to reduced neuroblastoma cell proliferation and increased differentiation. These changes in neuroblastoma phenotype are associated with decreased m6A deposition on transcripts involved in nervous system development and neuronal differentiation, with increased stability of target mRNAs. In preclinical studies, STM2457 treatment suppresses the growth of neuroblastoma tumors in vivo. Together, these results support the potential of METTL3/METTL14 complex inhibition as a therapeutic strategy against neuroblastoma.

High-valent metal-oxo species transformation and regulation by co-existing chloride: Reaction pathways and impacts on the generation of chlorinated by-products.

High-valent metal-oxo species (HMOS) have been extensively recognized in advanced oxidation processes (AOPs) owing to their high selectivity and high chemical utilization efficiency. However, the interactions between HMOS and halide ions in sewage wastewater are complicated, leading to ongoing debates on the intrinsic reactive species and impacts on remediation. Herein, we prepared three typical HMOS, including Fe(IV), Mn(V)-nitrilotriacetic acid complex (Mn(V)NTA) and Co(IV) through peroxymonosulfate (PMS) activation and comparatively studied their interactions with Cl- to reveal different reactive chlorine species (RCS) and the effects of HMOS types on RCS generation pathways. Our results show that the presence of Cl- alters the cleavage behavior of the peroxide OO bond in PMS and prohibits the generation of Fe(IV), spontaneously promoting SO4•- production and its subsequent transformation to secondary radicals like Cl• and Cl2•-. The generation and oxidation capacity of Mn(V)NTA was scarcely influenced by Cl-, while Cl- would substantially consume Co(IV) and promote HOCl generation through an oxygen-transfer reaction, evidenced by density functional theory (DFT) and deuterium oxide solvent exchange experiment. The two-electron-transfer standard redox potentials of Fe(IV), Mn(V)NTA and Co(IV) were calculated as 2.43, 2.55 and 2.85 V, respectively. Due to the different reactive species and pathways in the presence of Cl-, the amounts of chlorinated by-products followed the order of Co(II)/PMS > Fe(II)/PMS > Mn(II)NTA/PMS. Thus, this work renovates the knowledge of halide chemistry in HMOS-based systems and sheds light on the impact on the treatment of salinity-containing wastewater.

Mechanically treated Mn2O3 triggers peracetic acid activation for superior non-radical oxidation of micropollutants: Identification of reactive complexes.

This study used a simple mechanical ball milling strategy to significantly improve the ability of Mn2O3 to activate peracetic acid (PAA) for sustainable and efficient degradation of organic micropollutant (like bisphenol A, BPA). BPA was successfully removed and detoxified via PAA activation by the bm-Mn2O3 within 30 min under neutral environment, with the BPA degradation kinetic rate improved by 3.4 times. Satisfactory BPA removal efficiency can still be achieved over a wide pH range, in actual water and after reuse of bm-Mn2O3 for four cycles. The change in hydrophilicity of Mn2O3 after ball milling evidently elevated the affinity of Mn2O3 for binding to PAA, while the reduction in particle size exposed more active sites contributing partially to catalytic oxidation. Further analysis revealed that BPA oxidation in the ball mill-treated Mn2O3 (bm-Mn2O3)/PAA process mainly depends on the bm-Mn2O3-PAA complex (i.e., Mn(III)-OO(O)CCH3) mediated non-radical pathway rather than R-O• and Mn(IV). Especially, the existence of the Mn(III)-PAA complex was definitely verified by in situ Raman spectroscopy and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). Simultaneously, density functional theory calculations determined that PAA adsorbs readily on manganese sites thereby favoring the formation of Mn(III)-OO(O)CCH3 complexes. This study advances an in-depth understanding of the underlying mechanisms involved in the manganese oxide-catalyzed activation of PAA for superior non-radical oxidation of micropollutants.

5-Hydroxymethylcytosine in Cell-Free DNA Predicts Immunotherapy Response in Lung Cancer.

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03-0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02-0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8-94.5%) versus 0.0% (95% CI, 0.0-60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4-97.5%) versus 0.0% (95% CI, 0.0-36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer.

The YTHDF proteins display distinct cellular functions on m6A-modified RNA.

YTHDF proteins are main cytoplasmic 'reader' proteins of RNA N6-methyladenosine (m6A) methylation in mammals. They are largely responsible for m6A-mediated regulation in the cell cytosol by controlling both mRNA translation and degradation. Recent functional and mechanistic investigations of the YTHDF proteins revealed that these proteins have different functions to enable versatile regulation of the epitranscriptome. Their divergent functions largely originate from their different amino acid sequences in the low-complexity N termini. Consequently, they have different phase separation propensities and possess distinct post-translational modifications (PTMs). Different PTMs, subcellular localizations, and competition among partner proteins have emerged as three major mechanisms that control the functions of these YTHDF proteins. We also summarize recent progress on critical roles of these YTHDF proteins in anticancer immunity and the potential for targeting these proteins for developing new anticancer therapies.

A fine-scale Arabidopsis chromatin landscape reveals chromatin conformation-associated transcriptional dynamics.

Plants, as sessile organisms, deploy transcriptional dynamics for adapting to extreme growth conditions such as cold stress. Emerging evidence suggests that chromatin architecture contributes to transcriptional regulation. However, the relationship between chromatin architectural dynamics and transcriptional reprogramming in response to cold stress remains unclear. Here, we apply a chemical-crosslinking assisted proximity capture (CAP-C) method to elucidate the fine-scale chromatin landscape, revealing chromatin interactions within gene bodies closely associated with RNA polymerase II (Pol II) densities across initiation, pausing, and termination sites. We observe dynamic changes in chromatin interactions alongside Pol II activity alterations during cold stress, suggesting local chromatin dynamics may regulate Pol II activity. Notably, cold stress does not affect large-scale chromatin conformations. We further identify a comprehensive promoter-promoter interaction (PPI) network across the genome, potentially facilitating co-regulation of gene expression in response to cold stress. Our study deepens the understanding of chromatin conformation-associated gene regulation in plant response to cold.

Development of an Interpretable Deep Learning Model for Pathological Tumor Response Assessment After Neoadjuvant Therapy.

BACKGROUND: Neoadjuvant therapy followed by surgery has become the standard of care for locally advanced esophageal squamous cell carcinoma (ESCC) and accurate pathological response assessment is critical to assess the therapeutic efficacy. However, it can be laborious and inconsistency between different observers may occur. Hence, we aim to develop an interpretable deep-learning model for efficient pathological response assessment following neoadjuvant therapy in ESCC. METHODS: This retrospective study analyzed 337 ESCC resection specimens from 2020-2021 at the Pudong-Branch (Cohort 1) and 114 from 2021-2022 at the Puxi-Branch (External Cohort 2) of Fudan University Shanghai Cancer Center. Whole slide images (WSIs) from these two cohorts were generated using different scanning machines to test the ability of the model in handling color variations. Four pathologists independently assessed the pathological response. The senior pathologists annotated tumor beds and residual tumor percentages on WSIs to determine consensus labels. Furthermore, 1850 image patches were randomly extracted from Cohort 1 WSIs and binarily classified for tumor viability. A deep-learning model employing knowledge distillation was developed to automatically classify positive patches for each WSI and estimate the viable residual tumor percentages. Spatial heatmaps were output for model explanations and visualizations. RESULTS: The approach achieved high concordance with pathologist consensus, with an R^2 of 0.8437, a RAcc_0.1 of 0.7586, a RAcc_0.3 of 0.9885, which were comparable to two senior pathologists (R^2 of 0.9202/0.9619, RAcc_0.1 of 8506/0.9425, RAcc_0.3 of 1.000/1.000) and surpassing two junior pathologists (R^2 of 0.5592/0.5474, RAcc_0.1 of 0.5287/0.5287, RAcc_0.3 of 0.9080/0.9310). Visualizations enabled the localization of residual viable tumor to augment microscopic assessment. CONCLUSION: This work illustrates deep learning's potential for assisting pathological response assessment. Spatial heatmaps and patch examples provide intuitive explanations of model predictions, engendering clinical trust and adoption (Code and data will be available at https://github.com/WinnieLaugh/ESCC_Percentage once the paper has been conditionally accepted). Integrating interpretable computational pathology could help enhance the efficiency and consistency of tumor response assessment and empower precise oncology treatment decisions.