Host-Guest Doping Modulated Afterglow Emission of Fluoroquinolones for Their Separation-Free Detection and Discrimination.

Detection and discrimination of fluoroquinolones (FQs) are crucial for food safety but remain a formidable challenge due to their minor differences in molecular structures and the serious interferences from food matrices. Herein, we propose an afterglow assay for the detection and discrimination of FQs through modulating their room-temperature phosphorescence (RTP) and thermally activated delayed fluorescence (TADF) properties by a host-guest doping strategy. FQs were doped into the boric acid host, forming boronic anhydride structures and hydrogen bonds, which prompted the RTP and TADF performance of FQs by stabilizing their excited states, preventing triplet exciton quenching, and reducing the energy gap between singlet and triplet states. The FQs can be quantitatively detected through monitoring the afterglow intensity of host-guest systems, as low as 0.25 µg/mL. The differences in the afterglow intensity and emission lifetime allowed accurate discrimination of 11 types of FQs through pattern recognition methods. Aided by the delayed signal detection model of afterglow emission, the background signal and the interferences from food matrices were effectively eliminated, which endow the detection and discrimination of mixed FQs in commercial meat samples, without multiple-step separation processes.

Development and validation of a clinic-radiological model to predict tumor spread through air spaces in stage I lung adenocarcinoma.

OBJECTIVES: Tumor spread through air spaces (STAS) is associated with poor prognosis and impacts surgical options. We aimed to develop a user-friendly model based on 2-[18F] FDG PET/CT to predict STAS in stage I lung adenocarcinoma (LAC). MATERIALS AND METHODS: A total of 466 stage I LAC patients who underwent 2-[18F] FDG PET/CT examination and resection surgery were retrospectively enrolled. They were split into a training cohort (n = 232, 20.3% STAS-positive), a validation cohort (n = 122, 27.0% STAS-positive), and a test cohort (n = 112, 29.5% STAS-positive) according to chronological order. Some commonly used clinical data, visualized CT features, and SUVmax were analyzed to identify independent predictors of STAS. A prediction model was built using the independent predictors and validated using the three chronologically separated cohorts. Model performance was assessed using ROC curves and calculations of AUC. RESULTS: The differences in age (P = 0.009), lesion density subtype (P < 0.001), spiculation sign (P < 0.001), bronchus truncation sign (P = 0.001), and SUVmax (P < 0.001) between the positive and negative groups were statistically significant. Age ≥ 56 years [OR(95%CI):3.310(1.150-9.530), P = 0.027], lesion density subtype (P = 0.004) and SUVmax ≥ 2.5 g/ml [OR(95%CI):3.268(1.021-1.356), P = 0.005] were the independent factors predicting STAS. Logistic regression was used to build the A-D-S (Age-Density-SUVmax) prediction model, and the AUCs were 0.808, 0.786 and 0.806 in the training, validation, and test cohorts, respectively. CONCLUSIONS: STAS was more likely to occur in older patients, in solid lesions and higher SUVmax in stage I LAC. The PET/CT-based A-D-S prediction model is easy to use and has a high level of reliability in diagnosing.

Sex Differences in Coronary Inflammation and Atherosclerosis Phenotypes in Response to Imaging Marker of Stress-Related Neural Activity.

BACKGROUND: Sex-specific differences in coronary phenotypes in response to stress have not been elucidated. This study investigated the sex-specific differences in the coronary computed tomography angiography-assessed coronary response to mental stress. METHODS: This retrospective study included patients with coronary artery disease and without cancer who underwent resting 18F-fluorodexoyglucose positron emission tomography/computed tomography and coronary computed tomography angiography within 3 months. 18F-flourodeoxyglucose resting amygdalar uptake, an imaging biomarker of stress-related neural activity, coronary inflammation (fat attenuation index), and high-risk plaque characteristics were assessed by coronary computed tomography angiography. Their correlation and prognostic values were assessed according to sex. RESULTS: A total of 364 participants (27.7% women and 72.3% men) were enrolled. Among those with heightened stress-related neural activity, women were more likely to have a higher fat attenuation index (43.0% versus 24.0%; P=0.004), while men had a higher frequency of high-risk plaques (53.7% versus 39.3%; P=0.036). High amygdalar 18F-flourodeoxyglucose uptake (B-coefficient [SE], 3.62 [0.21]; P<0.001) was selected as the strongest predictor of fat attenuation index in a fully adjusted linear regression model in women, and the first-order interaction term consisting of sex and stress-related neural activity was significant (P<0.001). Those with enhanced imaging biomarkers of stress-related neural activity showed increased risk of major adverse cardiovascular event both in women (24.5% versus 5.1%; adjusted hazard ratio, 3.62 [95% CI, 1.14-17.14]; P=0.039) and men (17.2% versus 6.9%; adjusted hazard ratio, 2.72 [95% CI, 1.10-6.69]; P=0.030). CONCLUSIONS: Imaging-assessed stress-related neural activity carried prognostic values irrespective of sex; however, a sex-specific mechanism linking psychological stress to coronary plaque phenotypes existed in the current hypothesis-generating study. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05545618.

Cobalt oxyhydroxide nanosheet-modulated ratiometric fluorescence platform for the selective detection of malachite green in fish.

A ratiometric fluorescence platform was developed based on the cobalt oxyhydroxide (CoOOH) nanosheet-modulated fluorescence response of blue emissive copper nanoclusters (Cu NCs) and yellow emissive o-phenylenediamine (OPD). CoOOH nanosheets showed dual function of strong absorption and oxidation ability, which can effectively quench the blue fluorescence of Cu NCs, with an excitation and emission peak maximum at 390 and 450 nm, respectively , and transfer the OPD into yellow fluorescence products, with an excitation and emission peak maximum at 390 and 560 nm, respectively. Upon introducing butyrylcholinesterase (BChE) and its substrates, CoOOH nanosheets were decomposed into Co2+, and malachite green (MG) showed strong inhibition ability to this  process. This resulted in the obvious difference on the ratio of blue and yellow fluorescence recorded on the system in the presence and absence of MG, which was utilized for the quantitative detection of MG, with a limit of detection of 0.140 µM and a coefficient of variation of 3.5%. The fluorescence ratiometric assay showed excellent detection performances in practical sample analysis.

Detection and discrimination of glutathione among biological thiols based on oxalyl dihydrazide decorated sulfur nanodots.

The quantitative detection and discrimination of glutathione (GSH) were achieved based on oxalyl dihydrazide (ODH) decorated sulfur nanodots. ODH resulted in the aggregation and fluorescence quenching of the sulfur nanodots, and GSH selectively triggered fluorescence recovery through forming stronger hydrogen bonds with ODH than other biological thiols.

Fabrication of highly luminescent and thermally stable composites of sulfur nanodots through surface modification and assembly.

Sulfur nanodots (S-dots) have emerged as a promising luminescent material to excel over traditional heavy metal-based quantum dots. However, their relatively low emission efficiency and poor thermal stability in the solid state have limited their wide applications in photoelectric devices. In this work, highly luminescent, with a photoluminescence quantum yield higher than 50%, and thermally stable composites of S-dots were produced through modulating their surface states and aggregation behaviors by introducing pyromellitic dianhydride (PMDA) and benzoyleneurea (BEU), respectively. PMDA eliminated the relatively short-lived surface states and defects on the surface of S-dots and BEU regulated the aggregation states and facilitated the energy transfer from BEU to S-dots. The as-obtained composites also showed significantly improved thermal stability compared to S-dots, aided by the hydrophobic chemical groups and dense matrix of PMDA and BEU, which extended their applications in fabricating light-emitting diodes. Our presented results provide a new approach to produce highly luminescent S-dots, which widen their applications in the fields of bioimaging, sensing, photoelectric devices, and environmental science.

Low 18F-fluorodeoxyglucose dose positron emission tomography assisted by a deep-learning image-denoising technique in patients with lymphoma.

Background: Patients with lymphoma receive multiple positron emission tomography/computed tomography (PET/CT) exams for monitoring of the therapeutic response. With PET imaging, a reduced level of injected fluorine-18 fluorodeoxyglucose ([18F]FDG) activity can be administered while maintaining the image quality. In this study, we investigated the efficacy of applying a deep learning (DL) denoising-technique on image quality and the quantification of metabolic parameters and Deauville score (DS) of a low [18F]FDG dose PET in patients with lymphoma. Methods: This study retrospectively enrolled 62 patients who underwent [18F]FDG PET scans. The low-dose (LD) data were simulated by taking a 50% duration of routine-dose (RD) PET list-mode data in the reconstruction, and a U-Net-based denoising neural network was applied to improve the images of LD PET. The visual image quality score (1 = undiagnostic, 5 = excellent) and DS were assessed in all patients by nuclear radiologists. The maximum, mean, and standard deviation (SD) of the standardized uptake value (SUV) in the liver and mediastinum were measured. In addition, lesions in some patients were segmented using a fixed threshold of 2.5, and their SUV, metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG) were measured. The correlation coefficient and limits of agreement between the RD and LD group were analyzed. Results: The visual image quality of the LD group was improved compared with the RD group. The DS was similar between the RD and LD group, and the negative (DS 1-3) and positive (DS 4-5) results remained unchanged. The correlation coefficients of SUV in the liver, mediastinum, and lesions were all >0.85. The mean differences of SUVmax and SUVmean between the RD and LD groups, respectively, were 0.22 [95% confidence interval (CI): -0.19 to 0.64] and 0.02 (95% CI: -0.17 to 0.20) in the liver, 0.13 (95% CI: -0.17 to 0.42) and 0.02 (95% CI: -0.12 to 0.16) in the mediastinum, and -0.75 (95% CI: -3.42 to 1.91), and -0.13 (95% CI: -0.57 to 0.31) in lesions. The mean differences in MTV and TLG were 0.85 (95% CI: -2.27 to 3.98) and 4.06 (95% CI: -20.53 to 28.64) between the RD and LD groups. Conclusions: The DL denoising technique enables accurate tumor assessment and quantification with LD [18F]FDG PET imaging in patients with lymphoma.

Solitary bone plasmacytoma of spine with involvement of intervertebral disk: a case report and literature review.

Primary malignant bone tumors of the spine are exceedingly rare, with solitary bone plasmacytoma (SBP) representing approximately 30% of all cases. Radiological assessments are crucial for localizing SBP and for ruling out a diagnosis of multiple myeloma (MM). Imaging features resembling a "mini-brain" appear to be distinctive for SBP. Vertebral lesions accompanied by adjacent disc space involvement typically suggest spinal infections, while the potential for SBP involvement is often overlooked. We present a case of a 61-year-old female with SBP who exhibited thoraco-lumbar spine destruction and adjacent disc space involvement. The patient sought treatment at our medical center due to lumbodorsal pain radiating bilaterally to the inguinal regions. Radiological findings revealed an osteolytic lesion involving the intervertebral disc, making it challenging to distinguish between tumor and inflammation. A biopsy of the vertebral lesion confirmed the diagnosis of SBP, which was further supported by laboratory results. Post-diagnosis, the patient underwent radiotherapy, receiving a total dose of 4000 Gy, which alleviated her symptoms. We also provide a comprehensive literature review on SBP with disc involvement to aid both clinical and radiological diagnoses.

LoC-SERS platform for rapid and sensitive detection of colorectal cancer protein biomarkers.

Colorectal cancer (CRC) remains a significant contributor to the global mortality rate, and a single biomarker cannot meet the specificity required for CRC screening. To this end, we developed a multiplexed, pump-free surface-enhanced Raman scattering (SERS) microfluidic chip (LoC-SERS) using a one-step recognition release mechanism; the aptamer-functionalized novel Au nanocrown array (AuNCA) was used as the detection element embedded in the detection zone of the platform for rapid and specific detection of protein markers in multiple samples simultaneously. Here, the corresponding aptamer specifically captured the protein marker, causing the complementary strand of the aptamer carrying the Raman signal molecule to be shed, reducing the SERS signal. Based on this platform, sensitive and specific detection of the target can be accomplished within 15 min with detection limits of 0.031 pg/mL (hnRNP A1) and 0.057 pg/mL (S100P). Meanwhile, the platform was consistent with ELISA results when used to test clinical. By substituting different aptamers, this platform can provide a new solution for the rapid and sensitive detection of protein markers, which has promising applications in future disease detection.

Efficacy and safety of Lenvatinib-based combination therapies for patients with unresectable hepatocellular carcinoma: a single center retrospective study.

Background: Reports on Lenvatinib-based therapies show promising treatment outcomes for patients with unresectable hepatocellular carcinoma (uHCC). However, the effect and safety of Lenvatinib-based therapies still need to be further studies. Methods: This was a retrospective, single-center study on the safety and treatment efficacy of Lenvatinib-based combination therapies for uHCC Patients. The primary endpoints were progression-free survival (PFS) and overall survival (OS). The secondary endpoints were progressive disease (PD), stable disease (SD), partial response (PR), and complete response (CR). Results: Of 91 patients, there were 16 females and 75 males with uHCC who received systemic therapies based on Lenvatinib in our center. Forty-six patients (50.5%) received Lenvatinib combined with PD-1 antibody treatment. All these patients also received local therapy with the exception of 2 patients. The remaining 36 patinets received Lenvatinib combined with transcatheter arterial chemoembolization (TACE), 1 patient treated Lenvatinib combined with radiotherapy, 8 patients received Lenvatinib alone. At a median treatment time of 8 months, the objective response rate (ORR) of the entire cohort was 58.2% (53 patients), including 7 patients with CR and 46 patients with PR. 21 patients (23.1%) had SD. The disease control rate (DCR) of all patients was 81.3% (74 patients). However, 17 patients (18.7%) developed PD. The 1- and 2-year cumulative OS rates for the entire cohort were 66.8% and 39.3%, while the corresponding PFS rates were 38.0% and 17.1%, respectively. Univariate and multivariate Cox regression analysis revealed multiple tumor sites to be an independent OS risk factor for uHCC patients (HR=2.204, 95% CI=1.104-4.399, P=0.025). The most frequently reported adverse events in all patients were AST elevation (51.6%), followed by hypertension (33.0%), ALT elevation (26.4%), and decreased appetite (25.3%). After a combination treatment of Lenvatinib-based therapies, 15 patients met the criteria for salvage liver resection and underwent down-staging hepatectomy with a curative intent. The combination of PD-1 treatment was not very effective in improving the prognosis of uHCC patients treated with Lenvatinib combined with TACE. Conclusion: Our study demonstrated that a proportive of patients benefited from Lenvatinib-based combination therapies with manageable safety profiles, allowing these patients to undergo downstaging surgery with curative intent.

Stress-Related Neural Activity Associates With Coronary Plaque Vulnerability and Subsequent Cardiovascular Events.

BACKGROUND: Stress-related neural activity (SNA) assessed by amygdalar activity can predict cardiovascular events. However, its mechanistic linkage with plaque vulnerability is not fully elucidated. OBJECTIVES: The authors aimed to investigate the association of SNA with coronary plaque morphologic and inflammatory features as well as their ability in predicting major adverse cardiovascular events (MACE). METHODS: A total of 299 patients with coronary artery disease (CAD) and without cancer underwent 18F-fluorodexoyglucose positron emission tomography/computed tomography (PET/CT) and available coronary computed tomographic angiography (CCTA) between January 1, 2013, and December 31, 2020. SNA and bone-marrow activity (BMA) were assessed with validated methods. Coronary inflammation (fat attenuation index [FAI]) and high-risk plaque (HRP) characteristics were assessed by CCTA. Relations between these features were analyzed. Relations between SNA and MACE were assessed with Cox models, log-rank tests, and mediation (path) analyses. RESULTS: SNA was significant correlated with BMA (r = 0.39; P < 0.001) and FAI (r = 0.49; P < 0.001). Patients with heightened SNA are more likely to have HRP (40.7% vs 23.5%; P = 0.002) and increase risk of MACE (17.2% vs 5.1%, adjusted HR 3.22; 95% CI: 1.31-7.93; P = 0.011). Mediation analysis suggested that higher SNA associates with MACE via a serial mechanism involving BMA, FAI, and HRP. CONCLUSIONS: SNA is significantly correlated with FAI and HRP in patients with CAD. Furthermore, such neural activity was associated with MACE, which was mediated in part by leukopoietic activity in the bone marrow, coronary inflammation, and plaque vulnerability.

A CT-based deep learning radiomics nomogram outperforms the existing prognostic models for outcome prediction in clear cell renal cell carcinoma: a multicenter study.

OBJECTIVES: To develop and validate a CT-based deep learning radiomics nomogram (DLRN) for outcome prediction in clear cell renal cell carcinoma (ccRCC), and its performance was compared with the Stage, Size, Grade, and Necrosis (SSIGN) score, the University of California, Los Angeles, Integrated Staging System (UISS), the Memorial Sloan-Kettering Cancer Center (MSKCC), and the International Metastatic Renal Cell Database Consortium (IMDC). METHODS: A multicenter of 799 localized (training/ test cohort, 558/241) and 45 metastatic ccRCC patients were studied. A DLRN was developed for predicting recurrence-free survival (RFS) in localized ccRCC patients, and another DLRN was developed for predicting overall survival (OS) in metastatic ccRCC patients. The performance of the two DLRNs was compared with that of the SSIGN, UISS, MSKCC, and IMDC. Model performance was assessed with Kaplan-Meier curves, time-dependent area under the curve (time-AUC), Harrell's concordance index (C-index), and decision curve analysis (DCA). RESULTS: In the test cohort, the DLRN achieved higher time-AUCs (0.921, 0.911, and 0.900 for 1, 3, and 5 years, respectively), C-index (0.883), and net benefit than SSIGN and UISS in predicting RFS for localized ccRCC patients. The DLRN provided higher time-AUCs (0.594, 0.649, and 0.754 for 1, 3, and 5 years, respectively) than MSKCC and IMDC in predicting OS for metastatic ccRCC patients. CONCLUSIONS: The DLRN can accurately predict outcomes and outperformed the existing prognostic models in ccRCC patients. CLINICAL RELEVANCE STATEMENT: This deep learning radiomics nomogram may facilitate individualized treatment, surveillance, and adjuvant trial design for patients with clear cell renal cell carcinoma. KEY POINTS: • SSIGN, UISS, MSKCC, and IMDC may be insufficient for outcome prediction in ccRCC patients. • Radiomics and deep learning allow for the characterization of tumor heterogeneity. • The CT-based deep learning radiomics nomogram outperforms the existing prognostic models in ccRCC outcome prediction.

Sensitive detection of butyrylcholinesterase activity based on a stimuli-responsive fluorescence reaction.

A fluorogenic reaction between the chelate of Mn(II)-citric acid and terephthalic acid (PTA) was discovered, which was carried out through heating the aqueous mixture of Mn2+, citric acid and PTA. Detailed investigations indicated the reaction products were 2-hydroxyterephthalic acid (PTA-OH), which was attributed to the reaction between PTA and OH, formed by the triggering of Mn(II)-citric acid in the presence of dissolved O2. PTA-OH showed a strong blue fluorescence, peaked at 420 nm, and the fluorescence intensity presented a sensitive response to pH of the reaction system. Based on these mechanisms, the fluorogenic reaction was used for the detection of butyrylcholinesterase activity, achieving a detection limit of 0.15 U/L. The detection strategy was successfully applied in human serum samples, and it was also extended for the detection of organophosphorus pesticides and radical scavengers. Such a facile fluorogenic reaction and its stimuli-responsive properties offered an effective tool for designing detection pathways in the fields of clinical diagnosis, environmental monitoring and bioimaging.

Prognostic value of metabolic tumor volume and lesion dissemination from baseline PET/CT in patients with diffuse large B-cell lymphoma: Further risk stratification of the group with low-risk and high-risk NCCN-IPI.

PURPOSE: The purpose of this study was to determine the prognostic value of metabolic tumor volume and lesion dissemination from baseline PET/CT in patients with diffuse large B-cell lymphoma (DLBCL) and the prognostic value of them in the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) subgroups. METHODS: A total of 113 patients who underwent 18F-FDG PET/CT examination in our institution were retrospectively collected. The MTV was measured by iterative adaptive algorithm. The location of the lesion was obtained according to its three-dimensional coordinates, and Dmax was obtained. SDmax is derived from Dmax standardized by body surface area (BSA). The X-tile method was used to determine the optimal cut-off values for MTV, Dmax and SDmax. Cox regression analysis was used to perform univariate and multivariate analyses. Patient survival rates were derived from Kaplan-Meier curves and compared using the log-rank test. RESULTS: The median follow-up time was 24 months. The median of MTV was 196.86 cm3 (range 2.54-2925.37 cm3), and the optimal cut-off value was 489 cm3. The median of SDmax was 0.25 m-1 (range 0.12-0.51 m-1), and the best cut-off value was 0.31 m-1. MTV and SDmax were independent prognostic factors of PFS (all P < 0.001). Combined with MTV and SDmax, the patients were divided into three groups, and the difference of PFS among the groups was statistically significant (P < 0.001), and was able to stratify the risk of NCCN-IPI patients in the low-risk (NCCN-IPI < 4) and high-risk (NCCN-IPI ≥ 4) groups (P = 0.001 and P = 0.031). CONCLUSION: MTV and SDmax are independent prognostic factors for PFS in DCBCL patients, which describe tumor burden and tumor dissemination characteristics, respectively. The combination of the two could facilitate risk stratification between the low-risk and high-risk NCCN-IPI groups.

Incremental value of radiomics-based heterogeneity to the existing risk criteria in predicting recurrence of hepatocellular carcinoma after liver transplantation.

OBJECTIVES: The aim of the study was to evaluate the association between the radiomics-based intratumoral heterogeneity (ITH) and the recurrence risk in hepatocellular carcinoma (HCC) patients after liver transplantation (LT), and to assess its incremental to the Milan, University of California San Francisco (UCSF), Metro-Ticket 2.0, and Hangzhou criteria. METHODS: A multicenter cohort of 196 HCC patients were investigated. The endpoint was recurrence-free survival (RFS) after LT. A CT-based radiomics signature (RS) was constructed and assessed in the whole cohort and in the subgroups stratified by the Milan, UCSF, Metro-Ticket 2.0, and Hangzhou criteria. The R-Milan, R-UCSF, R-Metro-Ticket 2.0, and R-Hangzhou nomograms which combined RS and the four existing risk criteria were developed respectively. The incremental value of RS to the four existing risk criteria in RFS prediction was evaluated. RESULTS: RS was significantly associated with RFS in the training and test cohorts as well as in the subgroups stratified by the existing risk criteria. The four combined nomograms showed better predictive capability than the existing risk criteria did with higher C-indices (R-Milan [training/test] vs. Milan, 0.745/0.765 vs. 0.677; R-USCF vs. USCF, 0.748/0.767 vs. 0.675; R-Metro-Ticket 2.0 vs. Metro-Ticket 2.0, 0.756/0.783 vs. 0.670; R-Hangzhou vs. Hangzhou, 0.751/0.760 vs. 0.691) and higher clinical net benefit. CONCLUSIONS: The radiomics-based ITH can predict outcomes and provide incremental value to the existing risk criteria in HCC patients after LT. Incorporating radiomics-based ITH in HCC risk criteria may facilitate candidate selection, surveillance, and adjuvant trial design. KEY POINTS: • Milan, USCF, Metro-Ticket 2.0, and Hangzhou criteria may be insufficient for outcome prediction in HCC after LT. • Radiomics allows for the characterization of tumor heterogeneity. • Radiomics adds incremental value to the existing criteria in outcome prediction.

Ratiometric Fluorescence Assay for Pyrophosphate Based on Sulfur Nanodots Decorated Metal-Organic Frameworks.

Selective and sensitive detection of inorganic pyrophosphate (PPi) are of great significance both for clinical applications and fundamental research. In this work, a ratiometric fluorescent probe was developed by decorating a porphyrin-based metal-organic framework (PCN-224) with sulfur nanodots (S-dots). The red-fluorescence of PCN-224 was significantly promoted (more than 6-fold) by S-dots through inhibiting molecular motion of porphyrin ligand, which also provided active sites for the detection of Cu2+ and PPi. Cu2+ could selectively quench the red-fluorescence of PCN-224 through coordination with porphyrin ligand, and the competition reaction between PPi and Cu2+ resulted in the decomposing of coordination and recovery of red-fluorescence. The blue-fluorescence from S-dots was deemed as effective reference, which provided a built-in correction in complex environments. Based on these photophysical properties, a ratiometric fluorescence assay was developed for the quantitative detection of Cu2+ and PPi, with a limit of detection of 0.11 and 2.66 µM, respectively. The accuracy and practical applications of assays were also demonstrated by detection in tap water and human serum samples.

Modulating Emission of Boric Acid into Highly Efficient and Color-Tunable Afterglow via Dehydration-Induced Through-Space Conjugation.

Inorganic boric acid (BA) is generally not considered an efficient afterglow material, and several groups have reported its extremely weak room-temperature phosphorescence (RTP) in the blue spectral region. It is discovered that heat treatment of BA results in increased afterglow intensity (27-fold increase) and prolonged emission lifetime (from 0.83 to 1.59 s), attributed to enhanced through-space conjugation (TSC) of BA. The afterglow intensity of BA can be increased further (≈415 folds) by introducing p-hydroxybenzoic acid (PHA), which contains a conjugated molecular motif, to further promote the TSC of the BA system. This combination results in the production of afterglow materials with a photoluminescence quantum yield of 83.8% and an emission lifetime of 2.01 s. In addition, a tunable multicolor afterglow in the 420-490 nm range is achieved owing to the enhancement of the RTP and thermally activated delayed fluorescence of PHA, where BA exerts a confinement effect on the guest molecules. Thus, this study demonstrates promising afterglow materials produced from extremely abundant and simple precursor materials for various applications.

N6-Methyladenosine Modification of ANLN Enhances Hepatocellular Carcinoma Bone Metastasis.

Bones are categorized as the second most prevalent location of extra-hepatic metastasis in Hepatocellular Carcinoma (HCC), which is linked to an extremely poor prognosis due to limited therapeutic options. N6-methyladenosine (m6A) is a prominent modification involved in HCC, but the exact mechanisms on how m6A modifications induce HCC bone metastases (BM) remain unclear. The key modulators responsible for the abundant m6A RNA modification-induced HCC BM was found to be the METTL3 and YTHDF1. The expression of Anillin actin-binding protein (ANLN) was dramatically higher in HCC with BM tissues, and its messenger RNA (mRNA) stability was enhanced via m6A epitranscriptomic regulation by METTL3 and YTHDF1. High METTL3 and YTHDF1 expression along with nuclear ANLN protein was clinically correlated with BM in HCC patients. Furthermore, HCC BM was attributed to over-expression of nuclear ANLN forming a transcriptional complex with SP1 which enhanced KIF2C transcriptional activity to activate the mTORC1 pathway, therefore increased the expression of RANKL and disproportionated RANKL-OPG expression in bone microenvironment leading to malignant neoplasms invade bone tissue. In addition, inhibition of ANLN m6A modification by DZNeP attenuated HCC BM. This data provides meaningful understanding of the modulation and association of m6A epitranscriptomic-regulated BM in HCC, and moreover, defines potentially valuable therapeutic targets.