MyD88 and Its Inhibitors in Cancer: Prospects and Challenges.

The interplay between the immune system and cancer underscores the central role of immunotherapy in cancer treatment. In this context, the innate immune system plays a critical role in preventing tumor invasion. Myeloid differentiation factor 88 (MyD88) is crucial for innate immunity, and activation of MyD88 promotes the production of inflammatory cytokines and induces infiltration, polarization, and immune escape of immune cells in the tumor microenvironment. Additionally, abnormal MyD88 signaling induces tumor cell proliferation and metastasis, which are closely associated with poor prognosis. Therefore, MyD88 could serve as a novel tumor biomarker and is a promising target for cancer therapy. Current strategies targeting MyD88 including inhibition of signaling pathways and protein multimerization, have made substantial progress, especially in inflammatory diseases and chronic inflammation-induced cancers. However, the specific role of MyD88 in regulating tumor immunity and tumorigenic mechanisms remains unclear. Therefore, this review describes the involvement of MyD88 in tumor immune escape and disease therapy. In addition, classical and non-classical MyD88 inhibitors were collated to provide insights into potential cancer treatment strategies. Despite several challenges and complexities, targeting MyD88 is a promising avenue for improving cancer treatment and has the potential to revolutionize patient outcomes.

A novel subtype based on driver methylation-transcription in lung adenocarcinoma.

AIMS: To identify driver methylation genes and a novel subtype of lung adenocarcinoma (LUAD) by multi-omics and elucidate its molecular features and clinical significance. METHODS: We collected LUAD patients from public databases, and identified driver methylation genes (DMGs) by MethSig and MethylMix algrothms. And novel driver methylation multi-omics subtypes were identified by similarity network fusion (SNF). Furthermore, the prognosis, tumor microenvironment (TME), molecular features and therapy efficiency among subtypes were comprehensively evaluated. RESULTS: 147 overlapped driver methylation were identified and validated. By integrating the mRNA expression and methylation of DMGs using SNF, four distinct patterns, termed as S1-S4, were characterized by differences in prognosis, biological features, and TME. The S2 subtype showed unfavorable prognosis. By comparing the characteristics of the DMGs subtypes with the traditional subtypes, S3 was concentrated in proximal-inflammatory (PI) subtype, and S4 was consisted of terminal respiratory unit (TRU) subtype and PI subtype. By analyzing TME and epithelial mesenchymal transition (EMT) features, increased immune infiltration and higher expression of immune checkpoint genes were found in S3 and S4. While S4 showed higher EMT score and expression of EMT associated genes, indicating S4 may not be as immunosensitive as the S3. Additionally, S3 had lower TIDE and higher IPS score, indicating its increased sensitivity to immunotherapy. CONCLUSION: The driver methylation-related subtypes of LUAD demonstrate prognostic predictive ability that could help inform treatment response and provide complementary information to the existing subtypes.

Enhancement of Mn2+, Fe2+ and NH4+-N removal by biochar synergistic strains combined with activated sludge in real wastewater treatment.

Acinetobacter sp. AL-6 combining with biochar was adapted in activated sludge (AS & co-system) to decontaminate Mn2+, Fe2+ and NH4+-N, and treat activated sludge (AS) for its activity and settling performance improvement. Specifically, the co-system promoted the growth of bacteria in the activated sludge, thus increasing its ability to nitrify and adsorb Mn2+ and Fe2+, resulting in the removal of high concentrations of NH4+-N, Mn2+, Fe2+ and COD in the reactor by 100%, 100%, 100%, and 96.8%, respectively. And the pH of wastewater was increased from 4 to 8.5 by co-system also facilitated the precipitation of Mn2+ and Fe2+. The MLVSS/MLSS ratio increased from 0.64 to 0.95 and SVI30 decreased from 92.54 to 1.54 after the addition of co-system, which indicated that biochar helped to improve the activity and settling performance of activated sludge and prevented it from being damaged by the compound Mn2+ and Fe2+. In addition, biochar promoted the increase of the tyrosine-like protein substance and humic acid-like organic matter in the sludge EPS, thus enhanced the ability of sludge to adsorb Mn2+ and Fe2+. Concretely, compared with AS group, the proteins content and polysaccharides content of the AS & co-system group were increased by 13.14 times and 6.30 times respectively. Further, microbial diversity analysis showed that more resistant bacteria and dominant bacteria Acinetobacter sp. AL-6 in sludge enhanced the nitrification and adsorption of manganese and iron under the promotion of biochar. Pre-eminently, the more effective AS & co-system were applied to the removal of actual electrolytic manganese slag leachate taken from the contaminated site, and the removal of NH4+-N, Mn2+, Fe2+ and COD remained high at 100%, 100%, 71.82% and 94.72%, respectively, revealing advanced value for high engineering applications of AS & co-system.

Adaptively leverage multiple real-world data sources for treatment effect estimation based on similarity.

The incorporation of real-world data (RWD) into medical product development and evaluation has exhibited consistent growth. However, there is no universally adopted method of how much information to borrow from external data. This paper proposes a study design methodology called Tree-based Monte Carlo (TMC) that dynamically integrates patients from various RWD sources to calculate the treatment effect based on the similarity between clinical trial and RWD. Initially, a propensity score is developed to gauge the resemblance between clinical trial data and each real-world dataset. Utilizing this similarity metric, we construct a hierarchical clustering tree that delineates varying degrees of similarity between each RWD source and the clinical trial data. Ultimately, a Gaussian process methodology is employed across this hierarchical clustering framework to synthesize the projected treatment effects of the external group. Simulation result shows that our clustering tree could successfully identify similarity. Data sources exhibiting greater similarity with clinical trial are accorded higher weights in treatment estimation process, while less congruent sources receive comparatively lower emphasis. Compared with another Bayesian method, meta-analytic predictive prior (MAP), our proposed method's estimator is closer to the true value and has smaller bias.

Development of a machine learning-based model for predicting individual responses to antihypertensive treatments.

BACKGROUND AND AIMS: Personalized antihypertensive drug selection is essential for optimizing hypertension management. The study aimed to develop a machine learning (ML) model to predict individual blood pressure (BP) responses to different antihypertensive medications. METHODS AND RESULTS: We used data from a pragmatic, cluster-randomized trial on hypertension management in China. Each patient's multiple visit records were included, and two consecutive visits were paired as the index and subsequent visits. The least absolute shrinkage and selection operator method was used to select index visit variables for predicting subsequent BP. The dataset was randomly divided into training and test sets in a 7:3 ratio. Model performance was evaluated using mean absolute error (MAE) and R-square in the test set. A total of 19,013 hypertension management visit records (6282 patients) were included. The mean age of the study population was 63.9 years, and 2657 (42.3%) were females. A total of 12 phenotypical features (age, sex, smoking within seven days, body mass index, waist circumference, index visit systolic BP, diastolic BP, heart rate, comorbidities of diabetes, dyslipidemia, coronary heart disease, and stroke), together with currently taking any prescribed antihypertensive medication regimens and visits time interval were selected to build the model. The Extreme Gradient Boost model performed best among all candidate algorithms, with an MAE of 8.57 mmHg and an R2 = 0.28 in the test set. CONCLUSION: The ML techniques exhibit significant potential for predicting individual responses to antihypertensive treatments, thereby aiding clinicians in achieving optimal BP control safely and efficiently. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03636334. Registered July 3, 2018, https://clinicaltrials.gov/study/NCT03636334.

Non-halogenated Solvent-Processed Organic Solar Cells with Approaching 20 % Efficiency and Improved Photostability.

The development of high-efficiency organic solar cells (OSCs) processed from non-halogenated solvents is crucially important for their scale-up industry production. However, owing to the difficulty of regulating molecular aggregation, there is a huge efficiency gap between non-halogenated and halogenated solvent processed OSCs. Herein, we fabricate o-xylene processed OSCs with approaching 20 % efficiency by incorporating a trimeric guest acceptor named Tri-V into the PM6:L8-BO-X host blend. The incorporation of Tri-V effectively restricts the excessive aggregation of L8-BO-X, regulates the molecular packing and optimizes the phase-separation morphology, which leads to mitigated trap density states, reduced energy loss and suppressed charge recombination. Consequently, the PM6:L8-BO-X:Tri-V-based device achieves an efficiency of 19.82 %, representing the highest efficiency for non-halogenated solvent-processed OSCs reported to date. Noticeably, with the addition of Tri-V, the ternary device shows an improved photostability than binary PM6:L8-BO-X-based device, and maintains 80 % of the initial efficiency after continuous illumination for 1380 h. This work provides a feasible approach for fabricating high-efficiency, stable, eco-friendly OSCs, and sheds new light on the large-scale industrial production of OSCs.

Highly dangerous road hazards are not immune from the low prevalence effect.

The low prevalence effect (LPE) is a cognitive limitation commonly found in visual search tasks, in which observers miss rare targets. Drivers looking for road hazards are also subject to the LPE. However, not all road hazards are equal; a paper bag floating down the road is much less dangerous than a rampaging moose. Here, we asked whether perceived hazardousness modulated the LPE. To examine this, we took a dataset in which 48 raters assessed the perceived dangerousness of hazards in recorded road videos (Song et al. in Behav Res Methods, 2023. https://doi.org/10.3758/s13428-023-02299-8 ) and correlated the ratings with data from a hazard detection task using the same stimuli with varying hazard prevalence rates (Kosovicheva et al. in Psychon Bull Rev 30(1):212-223, 2023. https://doi.org/10.3758/s13423-022-02159-0 ). We found that while hazard detectability increased monotonically with hazardousness ratings, the LPE was comparable across perceived hazardousness levels. Our findings are consistent with the decision criterion account of the LPE, in which target rarity induces a conservative shift in criterion. Importantly, feedback was necessary for a large and consistent LPE; when participants were not given feedback about their accuracy, the most dangerous hazards showed a non-significant LPE. However, eliminating feedback was not enough to induce the opposite of the LPE-prevalence induced concept change (Levari et al. in Science 360(6396):1465-1467, 2018. https://doi.org/10.1126/science.aap8731 ), in which participants adopt a more liberal criterion when instances of a category become rare. Our results suggest that the road hazard LPE may be somewhat affected by the inherent variability of driving situations, but is still observed for highly dangerous hazards.

Simple and Efficient Synthesis of Novel Tetramers with Enhanced Glass Transition Temperature for High-Performance and Stable Organic Solar Cells.

Oligomer acceptors in organic solar cells (OSCs) have garnered substantial attention owing to their impressive power conversion efficiency (PCE) and long-term stability. However, the simple and efficient synthesis of oligomer acceptors with higher glass transition temperatures (Tg ) remains a formidable challenge. In this study, we propose an innovative strategy for the synthesis of tetramers, denoted as Tet-n, with elevated Tg s, achieved through only two consecutive Stille coupling reactions. Importantly, our strategy significantly reduces the redundancy in reaction steps compared to conventional methods for linear tetramer synthesis, thereby improving both reaction efficiency and yield. Furthermore, the OSC based on PM6:Tet-1 attains a high PCE of 17.32 %, and the PM6:L8-BO:Tet-1 ternary device achieves an even more higher PCE of 19.31 %. Remarkably, the binary device based on the Tet-1 tetramer demonstrates outstanding operational stability, retaining 80 % of the initial efficiency (T80 ) even after 1706 h of continuous illumination, which is primarily attributed to the enhanced Tg (247 °C) and lower diffusion coefficient (1.56×10-27  cm2 s-1 ). This work demonstrates the effectiveness of our proposed approach in the straightforward and efficient synthesis of tetramers materials with higher Tg s, thus offering a viable pathway for developing high-efficiency and stable OSCs.

Road Hazard Stimuli: Annotated naturalistic road videos for studying hazard detection and scene perception.

Driving requires vision, yet there is little empirical data about how vision and cognition support safe driving. It is difficult to study perception during natural driving because the experimental rigor required would be dangerous and unethical to implement on the road. The driving environment is complex, dynamic, and immensely variable, making it extremely challenging to accurately replicate in simulation. Our proposed solution is to study vision using stimuli which reflect this inherent complexity by using footage of real driving situations. To this end, we curated a set of 750 crowd-sourced video clips (434 hazard and 316 no-hazard clips), which have been spatially, temporally, and categorically annotated. These annotations describe where the hazard appears, what it is, and when it occurs. In addition, perceived dangerousness changes from moment to moment and is not a simple binary detection judgement. To capture this more granular aspect of our stimuli, we asked 48 observers to rate the perceived hazardousness of 1356 brief video clips taken from these 750 source clips on a continuous scale. These ratings span the entire scale, have high interrater agreement, and are robust to driving history. This novel stimulus set is not only useful for understanding drivers' ability to detect hazards, but is also a tool for studying dynamic scene perception and other aspects of visual function. While this stimulus set was originally designed for behavioral studies, researchers interested in other areas such as traffic safety or computer vision may also find this dataset a useful resource.

Auxiliary sequential deposition enables 19%-efficiency organic solar cells processed from halogen-free solvents.

High-efficiency organic solar cells are often achieved using toxic halogenated solvents and additives that are constrained in organic solar cells industry. Therefore, it is important to develop materials or processing methods that enabled highly efficient organic solar cells processed by halogen free solvents. In this paper, we report an innovative processing method named auxiliary sequential deposition that enables 19%-efficiency organic solar cells processed by halogen free solvents. Our auxiliary sequential deposition method is different from the conventional blend casting or sequential deposition methods in that it involves an additional casting of dithieno[3,2-b:2',3'-d]thiophene between the sequential depositions of the donor (D18-Cl) and acceptor (L8-BO) layers. The auxiliary sequential deposition method enables dramatic performance enhancement from 15% to over 18% compared to the blend casting and sequential deposition methods. Furthermore, by incorporating a branched-chain-engineered acceptor called L8-BO-X, device performance can be boosted to over 19% due to increased intermolecular packing, representing top-tier values for green-solvent processed organic solar cells. Comprehensive morphological and time-resolved characterizations reveal that the superior blend morphology achieved through the auxiliary sequential deposition method promotes charge generation while simultaneously suppressing charge recombination. This research underscores the potential of the auxiliary sequential deposition method for fabricating highly efficient organic solar cells using environmentally friendly solvents.

FOXN Transcription Factors: Regulation and Significant Role in Cancer.

A growing number of studies have demonstrated that cancer development is closely linked to abnormal gene expression, including alterations in the transcriptional activity of transcription factors. The Forkhead box class N (FOXN) proteins FOXN1-6 form a highly conserved class of transcription factors, which have been shown in recent years to be involved in the regulation of malignant progression in a variety of cancers. FOXNs mediate cell proliferation, cell-cycle progression, cell differentiation, metabolic homeostasis, embryonic development, DNA damage repair, tumor angiogenesis, and other critical biological processes. Therefore, transcriptional dysregulation of FOXNs can directly affect cellular physiology and promote cancer development. Numerous studies have demonstrated that the transcriptional activity of FOXNs is regulated by protein-protein interactions, microRNAs (miRNA), and posttranslational modifications (PTM). However, the mechanisms underlying the molecular regulation of FOXNs in cancer development are unclear. Here, we reviewed the molecular regulatory mechanisms of FOXNs expression and activity, their role in the malignant progression of tumors, and their value for clinical applications in cancer therapy. This review may help design experimental studies involving FOXN transcription factors, and enhance their therapeutic potential as antitumor targets.

METTL14 reverses liver fibrosis by inhibiting NOVA2 through an m6A-YTHDF2-dependent mechanism.

BACKGROUND: N6-methyladenosine (m6A), the most prevalent internal RNA modification in eukaryotic cells, is dynamically regulated in response to a wide range of physiological and pathological states. Nonetheless, the involvement of METTL14-induced m6A in liver fibrosis (LF) has yet to be established. METHODS: In vitro, HSC cell lines with knock-down and overexpression of METTL14 were constructed, and the effects of METTL14 gene on the phenotypic function of activated HSCs were observed. The proliferation rate was measured by CCK8 and EDU, the cell proliferation cycle was measured by flow detector, the migration rate was measured by Transwell, and the contractility of F-actin was observed after phalloidin staining. The downstream target gene NOVA2 of METTL14 was screened by combined sequencing of MeRIP-seq and RNA-seq, combined with signal analysis. Adeno-associated virus (AAV) was injected into the tail vein in vivo to knock down the expression of METTL14, so as to further observe the role of METTL14 in the progress of LF. RESULTS: our research showed that the methylase METTL14 content was decreased in hepatic tissue from patients with LF, leading to a lowered degree of m6A modification. Functionally, we discovered that knocking down m6A methyltransferase METTL14 led to increased HSC activation and a substantial worsening of LF. Mechanically, as shown in a multiomics study of HSCs, depleting METTL14 levels decreased m6A deposition onNOVA2 mRNA transcripts, which prompted the activation of YTHDF2 to detect and degrade the decrease of NOVA2 mRNA. CONCLUSIONS: METTL14 functioned as a profibrotic gene by suppressing NOVA2 activity in a mechanism dependent on m6A-YTHDF2. Moreover, knocking down METTL14 exacerbated LF, while NOVA2 prevented its development and partly reversed the damage.

Facile, Versatile and Stepwise Synthesis of High-Performance Oligomer Acceptors for Stable Organic Solar Cells.

Oligomer acceptors have recently emerged as promising photovoltaic materials for achieving high power conversion efficiency (PCE) and long-term stability in organic solar cells (OSCs). However, the limited availability of diverse acceptors, resulting from the sole synthetic approach, has hindered their potential for future industrialization. In this study, we present a facile and effective stepwise approach that utilizes two consecutive Stille coupling reactions for the synthesis of oligomer acceptors. To demonstrate the feasibility of the novel approach, we successfully synthesize a trimer acceptor, Tri-Y6-OD, and further systematically investigate the impact of oligomerization on device performance and stability. The results reveal that this approach has significant advantages compared to the conventional method, including reduced formation of unwanted by-products and lower difficulties in purification. Remarkably, the OSC based on PM6 : Tri-Y6-OD achieves an impressive PCE of 18.03 % and maintains 80 % of the initial PCE (T80 ) for 1523 h under illumination, surpassing the performance of the corresponding small molecule acceptor Y6-OD-based device. Furthermore, the versatility of the synthetic strategy in obtaining diverse acceptors is further demonstrated. Overall, our findings provide a facile, versatile and stepwise way for synthesizing oligomer acceptors, thereby facilitating the development of stable and efficient OSCs.

Multifunctional Nanotheranostics for Dual-Modal Imaging-Guided Precision Therapy of Nasopharyngeal Carcinoma.

Currently, the low survival rate and poor prognosis of patients with nasopharyngeal carcinoma are ascribed to the lack of early and accurate diagnosis and resistance to radiotherapy. In parallel, the integration of imaging-guided diagnosis and precise treatment has gained much attention in the field of theranostic nanotechnology. However, constructing dual-modal imaging-guided nanotheranostics with desired imaging performance as well as great biocompatibility remains challenging. Therefore, we developed a simple but multifunctional nanotheranostic GdCPP for the early and accurate diagnosis and efficient treatment of nasopharyngeal carcinoma (NPC), which combined fluorescence imaging and magnetic resonance imaging (MRI) onto a single nanoplatform for imaging-guided subsequent photodynamic therapy (PDT). GdCPP had an appropriate particle size (81.93 ± 0.69 nm) and was highly stable, resulting in sufficient tumor accumulation, which along with massive reactive oxygen species (ROS) generation upon irradiation further significantly killed tumor cells. Moreover, GdCPP owned much stronger r1 relaxivity (9.396 mM-1 s-1) compared to clinically used Gd-DTPA (5.034 mM-1 s-1) and exhibited better T1WI MRI performance. Under dual-modal imaging-guided PDT, GdCPP achieved efficient therapeutic outcomes without causing any noticeable tissue damage. The results of in vitro and in vivo studies indicated that GdCPP may be a suitable candidate for dual-modal imaging-guided precision tumor therapy.

TMEM175: A lysosomal ion channel associated with neurological diseases.

Lysosomes are acidic intracellular organelles with autophagic functions that are critical for protein degradation and mitochondrial homeostasis, while abnormalities in lysosomal physiological functions are closely associated with neurological disorders. Transmembrane protein 175 (TMEM175), an ion channel in the lysosomal membrane that is essential for maintaining lysosomal acidity, has been proven to coordinate with V-ATPase to modulate the luminal pH of the lysosome to assist the digestion of abnormal proteins and organelles. However, there is considerable controversy about the characteristics of TMEM175. In this review, we introduce the research progress on the structural, modulatory, and functional properties of TMEM175, followed by evidence of its relevance for neurological disorders. Finally, we discuss the potential value of TMEM175 as a therapeutic target in the hope of providing new directions for the treatment of neurodegenerative diseases.

Discovery of tetrahydroisoquinolineindole derivatives as first dual PRMT5 inhibitors/hnRNP E1 upregulators: Design, synthesis and biological evaluation.

Protein arginine methyltransferase 5 (PRMT5) is an epigenetics related enzyme that has been validated as an important therapeutic target for treating various types of cancer. Upregulation of tumor suppressor hnRNP E1 has also been considered as an effective antitumor therapy. In this study, a series of tetrahydroisoquinolineindole hybrids were designed and prepared, and compounds 3m and 3s4 were found to be selective inhibitors of PRMT5 and upregulators of hnRNP E1. Molecular docking studies indicated that compounds 3m occupied the substrate site of PRMT5 and formed essential interactions with amino acid residues. Furthermore, compounds 3m and 3s4 exerted antiproliferative effects against A549 cells by inducing apoptosis and inhibiting cell migration. Importantly, silencing of hnRNP E1 eliminated the antitumor effect of 3m and 3s4 on the apoptosis and migration in A549 cells, suggesting a regulatory relationship between PRMT5 and hnRNP E1. Additionally, compound 3m exhibited high metabolic stability on human liver microsomes (T1/2 = 132.4 min). In SD rats, the bioavailability of 3m was 31.4%, and its PK profiles showed satisfactory AUC and Cmax values compared to the positive control. These results suggest that compound 3m is the first class of dual PRMT5 inhibitor and hnRNP E1 upregulator that deserves further investigation as a potential anticancer agent.

Efficacy of Near-Infrared Fluorescence Video-Assisted Thoracoscopic Surgery for Small Pulmonary Nodule Resection with Indocyanine Green Inhalation: A Randomized Clinical Trial.

BACKGROUND: Small pulmonary nodules (<3 cm) can sometimes be unrecognizable and nonpalpable in video-assisted thoracoscopic surgery (VATS). Near-infrared fluorescence (NIF) VATS after indocyanine green (ICG) inhalation may effectively guide surgeons to locate the nodules. OBJECTIVE: This study aimed to investigate the safety, feasibility, and efficacy of ICG inhalation-based NIF imaging for guiding small pulmonary nodule resections. METHODS: Between February and May 2021, the first-stage, non-randomized trial enrolled 21 patients with different nodule depth, ICG inhalation doses, post-inhalation surgery times, and nodule types at a tertiary referral hospital. Between May 2021 and May 2022, the second-stage randomized trial enrolled 56 patients, who were randomly assigned to the fluorescence VATS (FLVATS) or the white-light VATS (WLVATS) group. The ratio of effective guidance and the time consumption for nodule localization were compared. RESULTS: The first-stage trial proved this new method is safe and feasible, and established a standardized protocol with optimized nodule depth (≤1 cm), ICG dose (0.20-0.25 mg/kg), and surgery window (50-90 min after ICG inhalation). In the second-stage trial, the FLVATS achieved 87.1% helpful nodule localization guidance, which was significantly higher than the WLVATS (59.1%, p < 0.05). The mean nodule locating time (standard deviation) was 1.8 [0.9] and 3.3 [2.3] min, respectively. Surgeons adopting FLVATS were significantly faster (p < 0.01), especially when locating small ground-glass opacities (1.3 [0.6] min vs. 7.0 [3.5] min, p < 0.05). Five of 31 nodules (16.1%) were only detectable by FLVATS, whereas both white light and palpation failed. CONCLUSIONS: This new method is safe and feasible for small pulmonary nodule resection. It significantly improves nodule localization rates with less time consumption, and hence is highly worthy for clinical promotion. Clinical Trial Registration Chinese Clinical Trial Registry Identifier: ChiCTR2100047326.

Cryptotanshinone induces apoptosis of activated hepatic stellate cells via modulating endoplasmic reticulum stress.

BACKGROUND: Cryptotanshinone (CPT) has wide biological functions, including anti-oxidative, antifibrosis, and anti-inflammatory properties. However, the effect of CPT on hepatic fibrosis is unknown. AIM: To investigate the effects of CPT treatment on hepatic fibrosis and its underlying mechanism of action. METHODS: Hepatic stellate cells (HSCs) and normal hepatocytes were treated with different concentrations of CPT and salubrinal. The CCK-8 assay was used to determine cell viability. Flow cytometry was used to measure apoptosis and cell cycle arrest. Reverse transcription polymerase chain reaction (RT-PCR) and Western blot analyses were used to measure mRNA levels and protein expression of endoplasmic reticulum stress (ERS) signaling pathway related molecules, respectively. Carbon tetrachloride (CCL4) was used to induce in vivo hepatic fibrosis in mice. Mice were treated with CPT and salubrinal, and blood and liver samples were collected for histopathological examination. RESULTS: We found that CPT treatment significantly reduced fibrogenesis by modulating the synthesis and degradation of the extracellular matrix in vitro. CPT inhibited cell proliferation and induced cell cycle arrest at the G2/M phase in cultured HSCs. Furthermore, we found that CPT promoted apoptosis of activated HSCs by upregulating expression of ERS markers (CHOP and GRP78) and activating ERS pathway molecules (PERK, IRE1α, and ATF4), which were inhibited by salubrinal. Inhibition of ERS by salubrinal partially eliminated the therapeutic effect of CPT in our CCL4-induced hepatic fibrosis mouse model. CONCLUSION: CPT can promote apoptosis of HSCs and alleviate hepatic fibrosis through modulating the ERS pathway, which represents a promising strategy for treating hepatic fibrosis.

E2EFP-MIL: End-to-end and high-generalizability weakly supervised deep convolutional network for lung cancer classification from whole slide image.

Efficient and accurate distinction of histopathological subtype of lung cancer is quite critical for the individualized treatment. So far, artificial intelligence techniques have been developed, whose performance yet remained debatable on more heterogenous data, hindering their clinical deployment. Here, we propose an end-to-end, well-generalized and data-efficient weakly supervised deep learning-based method. The method, end-to-end feature pyramid deep multi-instance learning model (E2EFP-MIL), contains an iterative sampling module, a trainable feature pyramid module and a robust feature aggregation module. E2EFP-MIL uses end-to-end learning to extract generalized morphological features automatically and identify discriminative histomorphological patterns. This method is trained with 1007 whole slide images (WSIs) of lung cancer from TCGA, with AUCs of 0.95-0.97 in test sets. We validated E2EFP-MIL in 5 real-world external heterogenous cohorts including nearly 1600 WSIs from both United States and China with AUCs of 0.94-0.97, and found that 100-200 training images are enough to achieve an AUC of >0.9. E2EFP-MIL overperforms multiple state-of-the-art MIL-based methods with high accuracy and low hardware requirements. Excellent and robust results prove generalizability and effectiveness of E2EFP-MIL in clinical practice. Our code is available at https://github.com/raycaohmu/E2EFP-MIL.

An R-R-type MYB transcription factor promotes non-climacteric pepper fruit carotenoid pigment biosynthesis.

Carotenoids are major accessory pigments in the chloroplast, and they also act as phytohormones and volatile compound precursors to influence plant development and confer characteristic colours, affecting both the aesthetic and nutritional value of fruits. Carotenoid pigmentation in ripening fruits is highly dependent on developmental trajectories. Transcription factors incorporate developmental and phytohormone signalling to regulate the biosynthesis process. By contrast to the well-established pathways regulating ripening-related carotenoid biosynthesis in climacteric fruit, carotenoid regulation in non-climacteric fruit is poorly understood. Capsanthin is the primary carotenoid of non-climacteric pepper (Capsicum) fruit; its biosynthesis is tightly associated with fruit ripening, and it confers red pigmentation to the ripening fruit. In the present study, using a coexpression analysis, we identified an R-R-type MYB transcription factor, DIVARICATA1, and demonstrated its role in capsanthin biosynthesis. DIVARICATA1 encodes a nucleus-localised protein that functions primarily as a transcriptional activator. Functional analyses showed that DIVARICATA1 positively regulates carotenoid biosynthetic gene (CBG) transcript levels and capsanthin levels by directly binding to and activating CBG promoter transcription. Furthermore, an association analysis revealed a significant positive association between DIVARICATA1 transcription level and capsanthin content. ABA promotes capsanthin biosynthesis in a DIVARICATA1-dependent manner. Comparative transcriptomic analysis of DIVARICATA1 in Solanaceae plants showed that its function likely differs among species. Moreover, the pepper DIVARICATA1 gene could be regulated by the ripening regulator MADS-RIN. The present study illustrates the transcriptional regulation of capsanthin biosynthesis and offers a target for breeding peppers with high red colour intensity.