Microbial gatekeepers: unraveling the role of the gut microbiota enzyme DPP4 in diabetes management.

Wang et al. identified dipeptidyl peptidase 4 (DPP4) as a gut microbe-derived enzyme that impacts on host glucose metabolism. They further introduced a novel therapeutic, daurisoline-d4 (Dau-d4), a selective microbial DPP4 (mDPP4) inhibitor that shows promise in improving glucose tolerance, highlighting the potential of therapies that target both host enzymes and gut microbial enzymes.

Design of robust superhydrophobic surfaces.

The ability of superhydrophobic surfaces to stay dry, self-clean and avoid biofouling is attractive for applications in biotechnology, medicine and heat transfer1-10. Water droplets that contact these surfaces must have large apparent contact angles (greater than 150 degrees) and small roll-off angles (less than 10 degrees). This can be realized for surfaces that have low-surface-energy chemistry and micro- or nanoscale surface roughness, minimizing contact between the liquid and the solid surface11-17. However, rough surfaces-for which only a small fraction of the overall area is in contact with the liquid-experience high local pressures under mechanical load, making them fragile and highly susceptible to abrasion18. Additionally, abrasion exposes underlying materials and may change the local nature of the surface from hydrophobic to hydrophilic19, resulting in the pinning of water droplets to the surface. It has therefore been assumed that mechanical robustness and water repellency are mutually exclusive surface properties. Here we show that robust superhydrophobicity can be realized by structuring surfaces at two different length scales, with a nanostructure design to provide water repellency and a microstructure design to provide durability. The microstructure is an interconnected surface frame containing 'pockets' that house highly water-repellent and mechanically fragile nanostructures. This surface frame acts as 'armour', preventing the removal of the nanostructures by abradants that are larger than the frame size. We apply this strategy to various substrates-including silicon, ceramic, metal and transparent glass-and show that the water repellency of the resulting superhydrophobic surfaces is preserved even after abrasion by sandpaper and by a sharp steel blade. We suggest that this transparent, mechanically robust, self-cleaning glass could help to negate the dust-contamination issue that leads to a loss of efficiency in solar cells. Our design strategy could also guide the development of other materials that need to retain effective self-cleaning, anti-fouling or heat-transfer abilities in harsh operating environments.

TransIntegrator: capture nearly full protein-coding transcript variants via integrating Illumina and PacBio transcriptomes.

Genes have the ability to produce transcript variants that perform specific cellular functions. However, accurately detecting all transcript variants remains a long-standing challenge, especially when working with poorly annotated genomes or without a known genome. To address this issue, we have developed a new computational method, TransIntegrator, which enables transcriptome-wide detection of novel transcript variants. For this, we determined 10 Illumina sequencing transcriptomes and a PacBio full-length transcriptome for consecutive embryo development stages of amphioxus, a species of great evolutionary importance. Based on the transcriptomes, we employed TransIntegrator to create a comprehensive transcript variant library, namely iTranscriptome. The resulting iTrancriptome contained 91 915 distinct transcript variants, with an average of 2.4 variants per gene. This substantially improved current amphioxus genome annotation by expanding the number of genes from 21 954 to 38 777. Further analysis manifested that the gene expansion was largely ascribed to integration of multiple Illumina datasets instead of involving the PacBio data. Moreover, we demonstrated an example application of TransIntegrator, via generating iTrancriptome, in aiding accurate transcriptome assembly, which significantly outperformed other hybrid methods such as IDP-denovo and Trinity. For user convenience, we have deposited the source codes of TransIntegrator on GitHub as well as a conda package in Anaconda. In summary, this study proposes an affordable but efficient method for reliable transcriptomic research in most species.

Recent infection with SARS-CoV-2 in donors was associated with a higher incidence of acute graft-versus-host disease in recipients undergoing allogeneic haematopoietic stem cell transplantation.

The global pandemic has resulted in the common occurrence of SARS-CoV-2 infection in the population. In the post-pandemic era, it is imperative to understand the influence of donor SARS-CoV-2 infection on outcomes after allogeneic haematopoietic stem cell transplantation (allo-HSCT). We retrospectively analysed allo-HSCTs from donors with mild SARS-CoV-2 infection or early recovery stage (ERS) (group 1, n = 65) and late recovery stage (group 2, n = 120). Additionally, we included allo-HSCT from donors without prior SARS-CoV-2 infection as group 0 (n = 194). Transplants from donors with different SARS-CoV-2 infection status had comparable primary engraftment and survival rates. However, group 1 had higher incidences of acute graft-versus-host disease (aGvHD), grade II-IV (41.5% vs. 28.1% in group 0 [p = 0.014] and 30.6% in group 2 [p = 0.067]) and grade III-IV (22.2% vs. 9.6% [p = 0.004] in group 0 and 12.2% in group 2 [p = 0.049]). Conversely, the risk of aGvHD in group 2 was similar to that in group 0 (p > 0.5). Multivariable analysis identified group 1 associated with grade II-IV (hazard ratio [HR] 2.307, p = 0.010) and grade III-IV (HR 2.962, p = 0.001) aGvHD, which yielded no significant risk factors for survival. In conclusion, we preliminarily demonstrated donors in the active infection state or ERS of mild SARS-CoV-2 infection were associated with higher incidences of aGvHD in transplants from related donors.

Multitask Deep Learning-Based Whole-Process System for Automatic Diagnosis of Breast Lesions and Axillary Lymph Node Metastasis Discrimination from Dynamic Contrast-Enhanced-MRI: A Multicenter Study.

BACKGROUND: Accurate diagnosis of breast lesions and discrimination of axillary lymph node (ALN) metastases largely depend on radiologist experience. PURPOSE: To develop a deep learning-based whole-process system (DLWPS) for segmentation and diagnosis of breast lesions and discrimination of ALN metastasis. STUDY TYPE: Retrospective. POPULATION: 1760 breast patients, who were divided into training and validation sets (1110 patients), internal (476 patients), and external (174 patients) test sets. FIELD STRENGTH/SEQUENCE: 3.0T/dynamic contrast-enhanced (DCE)-MRI sequence. ASSESSMENT: DLWPS was developed using segmentation and classification models. The DLWPS-based segmentation model was developed by the U-Net framework, which combined the attention module and the edge feature extraction module. The average score of the output scores of three networks was used as the result of the DLWPS-based classification model. Moreover, the radiologists' diagnosis without and with the DLWPS-assistance was explored. To reveal the underlying biological basis of DLWPS, genetic analysis was performed based on RNA-sequencing data. STATISTICAL TESTS: Dice similarity coefficient (DI), area under receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and kappa value. RESULTS: The segmentation model reached a DI of 0.828 and 0.813 in the internal and external test sets, respectively. Within the breast lesions diagnosis, the DLWPS achieved AUCs of 0.973 in internal test set and 0.936 in external test set. For ALN metastasis discrimination, the DLWPS achieved AUCs of 0.927 in internal test set and 0.917 in external test set. The agreement of radiologists improved with the DLWPS-assistance from 0.547 to 0.794, and from 0.848 to 0.892 in breast lesions diagnosis and ALN metastasis discrimination, respectively. Additionally, 10 breast cancers with ALN metastasis were associated with pathways of aerobic electron transport chain and cytoplasmic translation. DATA CONCLUSION: The performance of DLWPS indicates that it can promote radiologists in the judgment of breast lesions and ALN metastasis and nonmetastasis. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 3.

Pedigree Analysis of Nonclassical Cholesteryl Ester Storage Disease with Dominant Inheritance in a LIPA I378T Heterozygous Carrier.

BACKGROUND: Cholesterol ester storage disorder (CESD; OMIM: 278,000) was formerly assumed to be an autosomal recessive allelic genetic condition connected to diminished lysosomal acid lipase (LAL) activity due to LIPA gene abnormalities. CESD is characterized by abnormal liver function and lipid metabolism, and in severe cases, liver failure can occur leading to death. In this study, one Chinese nonclassical CESD pedigree with dominant inheritance was phenotyped and analyzed for the corresponding gene alterations. METHODS: Seven males and eight females from nonclassical CESD pedigree were recruited. Clinical features and LAL activities were documented. Whole genome Next-generation sequencing (NGS) was used to screen candidate genes and mutations, Sanger sequencing confirmed predicted mutations, and qPCR detected LIPA mRNA expression. RESULTS: Eight individuals of the pedigree were speculatively thought to have CESD. LAL activity was discovered to be lowered in four living members of the pedigree, but undetectable in the other four deceased members who died of probable hepatic failure. Three of the four living relatives had abnormal lipid metabolism and all four had liver dysfunctions. By liver biopsy, the proband exhibited diffuse vesicular fatty changes in noticeably enlarged hepatocytes and Kupffer cell hyperplasia. Surprisingly, only a newly discovered heterozygous mutation, c.1133T>C (p. Ile378Thr) on LIPA, was found by gene sequencing in the proband. All living family members who carried the p.I378T variant displayed reduced LAL activity. CONCLUSIONS: Phenotypic analyses indicate that this may be an autosomal dominant nonclassical CESD pedigree with a LIPA gene mutation.

Effects of Qiye Shen'an Pian Combined with Glutamate and Vitamin B1 on Fatigue State, Immune Function and Quality of Life in Patients with Chronic Fatigue Syndrome.

Objective: To observe the effects of Qiye Shen'an Pian combined with ghrelin and vitamin B1 on the fatigue status, immune function, and quality of life of patients with chronic fatigue syndrome (CFS), focusing specifically on the efficacy of this combination therapy. Methods: In this prospective study, 106 CFS patients admitted from June 2021 to June 2023 were selected. Using a simple randomisation method, patients were divided into two groups. The conventional group received glutathione and vitamin B1 treatment, while the Qiye Shen'an group received an additional treatment with Qiye Shen'an Pian on top of the standard glutathione and vitamin B1, for a continuous period of 8 weeks. To assess treatment efficacy, we compared immune function-related indexes (such as CD4+, CD8+, CD4+/CD8+ ratio, NK cell ratio), free radical metabolism indexes (like lipid peroxide, catalytic enzyme, and superoxide dismutase levels), TCM symptom scores, FS-14 scores, and SPHERE scores between the two groups. Adverse reactions were also recorded and statistically analyzed. Results: Notable improvements were observed in both groups, with the Qiye Shen'an group showing particularly significant enhancements. Post-treatment immune function indicators revealed a greater decrease in CD8+ levels in the Qiye Shen'an group (P < .05), along with marked increases in CD4+, CD4+/CD8+ ratio, and NK cell ratio in both groups, more so in the Qiye Shen'an group (P < .05). Free radical metabolism indicators, including lipid peroxide levels, decreased in both groups, with a more significant reduction observed in the Qiye Shen'an group (P < .05). The levels of catalytic enzyme and superoxide dismutase increased in both groups, with a notably higher improvement in the Qiye Shen'an group (P < .05). In terms of TCM symptom scores, FS-14 scores, and SPHERE scores, both groups showed a reduction after treatment, with a more substantial decrease in the Qiye Shen'an group (P < .05). Conclusion: In this study, we observed that Qiye Shen'an Pian combined with glutathione and vitamin B1, produced significant improvements in immune function and antioxidant capacity in patients with chronic fatigue syndrome (CFS). Specifically, patients' CD4+, CD8+ levels, and superoxide dismutase (SOD) activity all showed positive changes after treatment. These changes are crucial for enhancing patients' disease resistance and reducing fatigue symptoms. Qiye Shen'an Pian combined with glutamine and vitamin B1 in the treatment of CFS can alleviate the fatigue state of patients, improve the immune function, enhance the antioxidant capacity of the body, and improve somatic and psychological health. These findings underscore the potential of this combination therapy in effectively managing chronic fatigue syndrome, offering a promising direction for future treatment strategies.

Impact of Plasmonic and Dielectric Substrates on the Whispering-Gallery Modes in Self-Assembled Fluorescent Semiconductor Polymer Microspheres.

In this work, the impact of metallic and dielectric conducting substrates, gold and indium tin oxide (ITO)-coated glass, on the whispering gallery modes (WGMs) of semiconductor π-conjugated polymer microspheres is investigated. Hyperspectral mapping was performed to obtain the excitation-position-dependent emission spectra of the microspheres. Substrate-dependent quenching of WGMs sensitive to mode polarization was observed and explained. On a glass substrate, both transverse-electric (TE) and transverse-magnetic (TM) WGMs are quenched due to frustrated total internal reflection. On a gold substrate, however, only the TM WGMs are allowed in symmetry to leak into surface plasmons. An atomically flat gold substrate with subwavelength slits was used to experimentally verify the leakage of WGMs into the surface plasmon polaritons (SPPs). This work provides insight into the damping mechanisms of WGMs in microspheres on metallic and dielectric substrates.

Effect of faba bean Vicia faba L. water/alcohol extract on growth performance, antioxidant capacity, textural properties, and collagen deposition in the swim bladder of juvenile Nibea coibor.

Faba bean has gained attention as a cost-effective protein source with the potential to enhance product quality (texture properties, collagen content, etc.) in fish. However, its anti-nutrition factor, high feed conversion ratio, poor growth performance, etc. limit the widely application as a dietary source, especially in carnivorous fish. The water or alcohol extract of faba bean might resolve the problem. In this study, the juvenile Nibea coibor, known for their high-protein, large-sized, and high-grade swim bladder, were fed with seven isoproteic and isolipid experimental diets with the additive of faba bean water extract (1.25%, 2.5%, and 5%) or faba bean alcohol extract (0.9%, 1.8%, and 3.6%), with a control group without faba bean extract. After the 10-week feeding trail, the growth, antioxidant capacity, textural properties, and collagen deposition of the swim bladder were analyzed. Results showed that the 1.25% faba bean water extract group could significantly promote growth, textural quality of the swim bladder, and have beneficial effects on antioxidant response of fish. Conversely, dietary supplementation of faba bean alcohol extract resulted in reduced growth performance in a dose-dependent manner. Furthermore, fish fed diet with 1.25% faba bean water extract exhibited increased collagen content and upregulated collagen-related gene expression in the swim bladder, which was consistent with the Masson stain analysis for collagen fiber. Our results suggested that the anti-nutrient factor and bioactive component of faba bean may mainly be enriched in alcohol extract and water extract of faba bean, respectively. Besides, the appropriate addition of water extract of faba bean may improve the texture quality of the swim bladder by promoting collagen deposition. This study would provide a theoretical basis for the formulated diets with faba bean extract to promote product quality of marine fish.

Clinical Assessment of Magnetic Resonance Spectroscopy and Diffusion-Weighted Imaging in Diffuse Glioma: Insights Into Histological Grading and IDH Classification.

PURPOSE: To assess the diagnostic utility of clinical magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) in distinguishing between histological grading and isocitrate dehydrogenase (IDH) classification in adult diffuse gliomas. METHODS: A retrospective analysis was conducted on 247 patients diagnosed with adult diffuse glioma. Experienced radiologists evaluated DWI and MRS images. The Kruskal-Wallis test examined differences in DWI and MRS-related parameters across histological grades, while the Mann-Whitney U test assessed molecular classification. Receiver Operating Characteristic (ROC) curves evaluated parameter effectiveness. Survival curves, stratified by histological grade and IDH classification, were constructed using the Kaplan-Meier test. RESULTS: The cohort comprised 141 males and 106 females, with ages ranging from 19 to 85 years. The Kruskal-Wallis test revealed significant differences in ADC mean, Cho/NAA, and Cho/Cr concerning glioma histological grade (P < .01). Subsequent application of Dunn's test showed significant differences in ADC mean among each histological grade (P < .01). Notably, Cho/NAA exhibited a marked distinction between grade 2 and grade 3/4 gliomas (P < .01). The Mann-Whitney U test indicated that only ADC mean showed statistical significance for IDH molecular classification (P < .01). ROC curves were constructed to demonstrate the effectiveness of the specified parameters. Survival curves were also delineated to portray survival outcomes categorized by histological grade and IDH classification. Conclusions: Clinical MRS demonstrates efficacy in glioma histological grading but faces challenges in IDH classification. Clinical DWI's ADC mean parameter shows significant distinctions in both histological grade and IDH classification.

Elucidation of the Roles of Water on the Reactivity of Surface Intermediates in Carboxylic Acid Ketonization on TiO2.

The effects of water on the carboxylic acid ketonization reaction over solid Lewis-acid catalysts were examined by nuclear magnetic resonance (NMR) spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), temperature-programmed desorption (TPD), and kinetic measurements. Acetic acid and propanoic acid were used as model compounds, and P25 TiO2 was used as a model catalyst to represent the anatase TiO2 since the rutile phase only contributes to <2.5% of the overall ketonization activity of P25 TiO2. The kinetic measurement showed that introducing H2O vapor in gaseous feed decreases the ketonization reaction rate by increasing the intrinsic activation barrier of gas-phase acetic acid on anatase TiO2. Quantitative TPD of acetic acid indicated that H2O does not compete with acetic acid for Lewis sites. Instead, as indicated by combined approaches of NMR and DRIFTS, H2O associates with the adsorbed acetate or acetic acid intermediates on the catalyst surface and alters their reactivities for the ketonization reaction. There are multiple species present on the anatase TiO2 surface upon carboxylic acid adsorption, including molecular carboxylic acid, monodentate carboxylate, and chelating/bridging bidentate carboxylates. The presence of H2O vapor increases the coverage of the less reactive bridging bidentate carboxylate associated with adsorbed H2O, leading to lower ketonization activity on hydrated anatase TiO2. Surface hydroxyl groups, which are consumed by interaction with carboxylic acid upon the formation of surface acetate species, do not impact the ketonization reaction.

Attention-based deep learning for breast lesions classification on contrast enhanced spectral mammography: a multicentre study.

BACKGROUND: This study aims to develop an attention-based deep learning model for distinguishing benign from malignant breast lesions on CESM. METHODS: Preoperative CESM images of 1239 patients, which were definitely diagnosed on pathology in a multicentre cohort, were divided into training and validation sets, internal and external test sets. The regions of interest of the breast lesions were outlined manually by a senior radiologist. We adopted three conventional convolutional neural networks (CNNs), namely, DenseNet 121, Xception, and ResNet 50, as the backbone architectures and incorporated the convolutional block attention module (CBAM) into them for classification. The performance of the models was analysed in terms of the receiver operating characteristic (ROC) curve, accuracy, the positive predictive value (PPV), the negative predictive value (NPV), the F1 score, the precision recall curve (PRC), and heat maps. The final models were compared with the diagnostic performance of conventional CNNs, radiomics models, and two radiologists with specialised breast imaging experience. RESULTS: The best-performing deep learning model, that is, the CBAM-based Xception, achieved an area under the ROC curve (AUC) of 0.970, a sensitivity of 0.848, a specificity of 1.000, and an accuracy of 0.891 on the external test set, which was higher than those of other CNNs, radiomics models, and radiologists. The PRC and the heat maps also indicated the favourable predictive performance of the attention-based CNN model. The diagnostic performance of two radiologists improved with deep learning assistance. CONCLUSIONS: Using an attention-based deep learning model based on CESM images can help to distinguishing benign from malignant breast lesions, and the diagnostic performance of radiologists improved with deep learning assistance.

Abnormal Graphitization Behavior in Near-Surface/Interface Region of Polymer-Derived Ceramics.

The in situ free carbon generated in polymer-derived ceramics (PDCs) plays a crucial role in their unique microstructure and resultant properties. This study advances a new phenomenon of graphitization of PDCs. Specifically, whether in micro-/nanoscale films or millimeter-scale bulks, the surface/interface radically changes the fate of carbon and the evolution of PDC nanodomains, promotes the graphitization of carbon, and evolves a free carbon enriched layer in the near-surface/interface region. Affected by the enrichment behavior of free carbon in the near-surface/interface region, PDCs exhibit highly abnormal properties such as the skin behavior and edge effect of the current. The current intensity in the near-surface/interface region of PDCs is orders of magnitude higher than that in its interior. Ultrahigh conductivity of up to 14.47 S cm-1 is obtained under the action of the interface and surface, which is 5-8 orders of magnitude higher than that of the bulk prepared under the same conditions. Such surface/interface interactions are of interest for the regulation of free carbon and its resultant properties, which are the core of PDC applications. Finally, the first PDC thin-film strain gauge that can survive a butane flame with a high temperature of up to ≈1300 °C is fabricated.

Random-modulated pulse lidar using a gain-switched semiconductor laser with a delayed self-homodyne interferometer.

We propose the generation of random-modulated pulses using a gain-switched semiconductor laser with a delayed self-homodyne interferometer (DSHI) for lidar applications. By emitting non-repetitive random-modulated pulses, ambiguity in ranging and interference in detection can be mitigated. When gain-switched, the wavelength of the laser fluctuates abruptly at the beginning of the pulse and then drops until it stabilizes toward its continuous-wave (CW) state. By beating the two pulses with instantaneous frequency detuning from the DSHI, pulses consisting of random and down-chirped modulations can be generated without any complex code generation and modulation. In this study, we investigate the waveforms and spectra of the random-modulated pulses generated under various homodyne delay lengths, switching currents, and pulsewidths. We characterize their signal-to-noise ratio (SNR), precision, and cross-correlation between consecutive pulses to evaluate their performance in lidar applications. For a good SNR of over 12 dB, the generated pulses have an optimal precision of approximately 1 mm in ranging, which is substantially better than the chaos-modulated pulses generated based on laser feedback dynamics. By establishing a random-modulated pulse lidar based on the proposed gain-switched homodyne scheme, we successfully demonstrate 3D imaging and profiling with good precision.

Mean platelet volume/platelet count ratio in combination with tumor markers in colorectal cancer: a retrospective clinical study.

BACKGROUND: Mean platelet volume (MPV) is a marker of platelet activation, which is usually negatively correlated with platelet count (PC). The ratio of MPV to PC (MPV/PC) has an essential role in the diagnosis of multiple malignancies. However, only a few studies investigated the value of MPV/PC in colorectal cancer (CRC) and the combination of MPV/PC with tumor markers in CRC. This retrospective clinical study aimed to evaluate the diagnostic value of MPV/PC and tumor markers (CA72-4, CA125, CA199) used alone or in combination in CRC. METHODS: 200 patients with CRC and 317 patients with colorectal benign polypus pathologically diagnosed during 2019/01/04 to 2022/06/30 were included. Hematological and pathological parameters of the above patients were collected, data were analyzed with Student's t-test, one-way ANOVA or Kruskal-Wallis H test and receiver operating characteristic (ROC) curve, and ROC curve was used to evaluate the diagnostic value of tumor markers and MPV/PC used alone or in combination in CRC. RESULTS: The MPV/PC in CRC group was significantly lower than the control group (P < 0.0001). Among the three tumor markers, higher CA125 was correlated with distant metastasis and lower differentiation (P < 0.05), increased CA72-4 indicated positive nerve invasion (P = 0.0174), and elevated CA199 was associated with lymphatic metastasis and positive vascular invasion (P < 0.05). For subgroups regarding tumor anatomical location, both CA125 and CA199 were higher in colon cancer group than rectum cancer group (P = 0.0322, P = 0.0094). MPV/PC was associated with tumor infiltration, regional lymph node metastasis, differentiation and nerve invasion (P < 0.05) and the combination of MPV/PC with the three tumor markers produced a larger AUC with higher sensitivity, specificity and Yuden index than MPV/PC or the three tumor markers used alone to distinguish between CRC and colorectal polyps. CONCLUSION: Preoperative MPV/PC in peripheral blood of patients with CRC was lower than the control group. Meanwhile, the combined detection of tumor markers with MPV/PC can improve the diagnostic value of CRC, revealing the potential of MPV/PC as a promising screening tool in CRC early diagnosis.

Time-dependent analysis of the impact on early cytomegalovirus reactivation of HLA mismatch and acute graft-versus-host disease after allogeneic hematopoietic cell transplantation from related donors in acquired aplastic anemia.

Cytomegalovirus (CMV) reactivation is an important issue in allogeneic hematopoietic cell transplantation (HCT). The incidence of early CMV reactivation is notably high in HLA-mismatched HCT. However, the interactions between HLA mismatch and acute graft-versus-host disease (aGvHD), a time-dependent event, make it methodologically challenging to evaluate the independent impact on CMV reactivation of the two variables. We retrospectively analyzed 355 patients with acquired aplastic anemia who received related donor transplants using a unified antithymocyte globulin-based platform. Patients were divided into group 1 (6/6 HLA match), group 2 (1-2/6 HLA allelic mismatch), and group 3 (3/6 HLA allelic mismatch). The impact of covariates was analyzed through two models: (1) time-dependent Cox and (2) dynamic landmarking analysis. The time-dependent Cox model showed that the HLA mismatch of 3/6 alleles (hazard ratio (HR) =1.852, P = .004) and aGvHD (HR = 1.009, P = .019) were independent risk factors for CMV reactivation. With the dynamic landmarking analysis, a higher HLA disparity correlated to increased early CMV reactivation (HR = 1.606, P = .001) at all time points. Developing aGvHD following HCT was generally associated with a higher incidence of CMV reactivation (HR = 1.623, P = .013), though its impact decreased with successive later landmark time points. In conclusion, our data suggest that the higher HLA disparity and aGvHD increases susceptibility to early CMV reactivation. In particular, the dynamic landmarking analysis demonstrated the time-varying effect of aGvHD on CMV reactivation, and HLA mismatch showed a profound impact over time following HCT.

Toward the next generation EGFR inhibitors: an overview of osimertinib resistance mediated by EGFR mutations in non-small cell lung cancer.

Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) is currently the standard first-line therapy for EGFR-mutated advanced non-small cell lung cancer (NSCLC). The life quality and survival of this subgroup of patients were constantly improving owing to the continuous iteration and optimization of EGFR-TKI. Osimertinib, an oral, third-generation, irreversible EGFR-TKI, was initially approved for the treatment of NSCLC patients carrying EGFR T790M mutations, and has currently become the dominant first-line targeted therapy for most EGFR mutant lung cancer. Unfortunately, resistance to osimertinib inevitably develops during the treatment and therefore limits its long-term effectiveness. For both fundamental and clinical researchers, it stands for a major challenge to reveal the mechanism, and a dire need to develop novel therapeutics to overcome the resistance. In this article, we focus on the acquired resistance to osimertinib caused by EGFR mutations which account for approximately 1/3 of all reported resistance mechanisms. We also review the proposed therapeutic strategies for each type of mutation conferring resistance to osimertinib and give an outlook to the development of the next generation EGFR inhibitors. Video Abstract.

TAK1 blockade as a therapy for retinal neovascularization.

Retinal neovascularization, or pathological angiogenesis in the retina, is a leading cause of blindness in developed countries. Transforming growth factor-ß-activated kinase 1 (TAK1) is a mitogen-activated protein kinase kinase kinase (MAPKKK) activated by TGF-ß1 and other proinflammatory cytokines. TAK1 is also a key mediator of proinflammatory signals and plays an important role in maintaining vascular integrity upon proinflammatory cytokine stimulation such as TNFα. However, its role in pathological angiogenesis, particularly in retinal neovascularization, remains unclear. Here, we investigate the regulatory role of TAK1 in human endothelial cells responding to inflammatory stimuli and in a rat model of oxygen-induced retinopathy (OIR) featured retinal neovascularization. Using TAK1 knockout human endothelial cells that subjected to inflammatory stimuli, transcriptome analysis revealed that TAK1 is required for activation of NFκB signaling and mediates its downstream gene expression related to endothelial activation and angiogenesis. Moreover, pharmacological inhibition of TAK1 by 5Z-7-oxozeaenol attenuated angiogenic activities of endothelial cells. Transcriptome analysis also revealed enrichment of TAK1-mediated NFκB signaling pathway in the retina of OIR rats and retinal neovascular membrane from patients with proliferative diabetic retinopathy. Intravitreal injection of 5Z-7-oxozeaenol significantly reduced hypoxia-induced inflammation and microglial activation, thus attenuating aberrant retinal angiogenesis in OIR rats. Our data suggest that inhibition of TAK1 may have therapeutic potential for the treatment of retinal neovascular pathologies.

Distinguishing common renal cell carcinomas from benign renal tumors based on machine learning: comparing various CT imaging phases, slices, tumor sizes, and ROI segmentation strategies.

OBJECTIVES: To determine whether a CT-based machine learning (ML) can differentiate benign renal tumors from renal cell carcinomas (RCCs) and improve radiologists' diagnostic performance, and evaluate the impact of variable CT imaging phases, slices, tumor sizes, and region of interest (ROI) segmentation strategies. METHODS: Patients with pathologically proven RCCs and benign renal tumors from our institution between 2008 and 2020 were included as the training dataset for ML model development and internal validation (including 418 RCCs and 78 benign tumors), and patients from two independent institutions and a public database (TCIA) were included as the external dataset for individual testing (including 262 RCCs and 47 benign tumors). Features were extracted from three-phase CT images. CatBoost was used for feature selection and ML model establishment. The area under the receiver operating characteristic curve (AUC) was used to assess the performance of the ML model. RESULTS: The ML model based on 3D images performed better than that based on 2D images, with the highest AUC of 0.81 and accuracy (ACC) of 0.86. All three radiologists achieved better performance by referring to the classifier's decision, with accuracies increasing from 0.82 to 0.87, 0.82 to 0.88, and 0.76 to 0.87. The ML model achieved higher negative predictive values (NPV, 0.82-0.99), and the radiologists achieved higher positive predictive values (PPV, 0.91-0.95). CONCLUSIONS: A ML classifier based on whole-tumor three-phase CT images can be a useful and promising tool for differentiating RCCs from benign renal tumors. The ML model also perfectly complements radiologist interpretations. KEY POINTS: • A machine learning classifier based on CT images could be a reliable way to differentiate RCCs from benign renal tumors. • The machine learning model perfectly complemented the radiologists' interpretations. • Subtle variances in ROI delineation had little effect on the performance of the ML classifier.

Intra- and peritumoral radiomics for predicting malignant BiRADS category 4 breast lesions on contrast-enhanced spectral mammography: a multicenter study.

OBJECTIVE: To construct and test a nomogram based on intra- and peritumoral radiomics and clinical factors for predicting malignant BiRADS 4 lesions on contrast-enhanced spectral mammography. METHODS: A total of 884 patients with BiRADS 4 lesions were enrolled from two centers. For each lesion, five ROIs were defined using the intratumoral region (ITR), peritumoral regions (PTRs) of 5 and 10 mm around the tumor, and ITR plus PTRs of 5 mm and 10 mm. Five radiomics signatures were established by LASSO after selecting features. A nomogram was built using selected signatures and clinical factors by multivariable logistic regression analysis. The performance of the nomogram was assessed with the AUC, decision curve analysis, and calibration curves, and also compared with the radiomics model, clinical model, and radiologists. RESULTS: The nomogram built by three radiomics signatures (constructed from ITR, 5 mm PTR, and ITR + 10 mm PTR) and two clinical factors (age and BiRADS category) showed powerful predictive ability in internal and external test sets with AUCs of 0.907 and 0.904, respectively. The calibration curves, decision curve analysis, showed favorable predictive performance of the nomogram. In addition, radiologists improved the diagnostic performance with the help of nomogram. CONCLUSION: The nomogram established via intratumoral and peritumoral radiomics features and clinical risk factors had the best performance in distinguishing benign and malignant BiRADS 4 lesions, which could help radiologists improve diagnostic capabilities. KEY POINTS: • Radiomics features from peritumoral regions in contrast-enhanced spectral mammography images may provide valuable information for the diagnosis of benign and malignant breast imaging reporting and data system category 4 breast lesions. • The nomogram incorporated intra- and peritumoral radiomics features and clinical variables have good application prospects in assisting clinical decision-makers.