Development and validation of a nomogram to predict poor efficacy of imatinib in the treatment of newly diagnosed chronic phase chronic myeloid leukemia patients.

Background: Imatinib is the most widely used tyrosine kinase inhibitor (TKI) in patients with newly diagnosed chronic-phase chronic myeloid leukemia(CML-CP). However, failure to achieve optimal response after imatinib administration, and subsequent switch to second-generation TKI therapy results in poor efficacy and induces drug resistance. In the present study, we developed and validated a nomogram to predict the efficacy of imatinib in the treatment of patients newly diagnosed with CML-CP in order to help clinicians truly select patients who need 2nd generation TKI during initial therapy and to supplement the risk score system. Methods: We retrospectively analyzed 156 patients newly diagnosed with CML-CP who met the inclusion criteria and were treated with imatinib at the Second Affiliated Hospital of Xi'an Jiao Tong University from January 2012 to June 2022. The patients were divided into a poor-response cohort (N = 60)and an optimal-response cohort (N = 43) based on whether they achieved major molecular remission (MMR) after 12 months of imatinib treatment. Using univariate and multivariate logistic regression analyses, we developed a chronic myeloid leukemia imatinib-poor treatment (CML-IMP) prognostic model using a nomogram considering characteristics like age, sex, HBG, splenic size, and ALP. The CML-IMP model was internally validated and compared with Sokal, Euro, EUTOS, and ELTS scores. Results: The area under the curve of the receiver operator characteristic curve (AUC)of 0.851 (95% CI 0.778-0.925) indicated satisfactory discriminatory ability of the nomogram. The calibration plot shows good consistency between the predicted and actual observations. The net reclassification index (NRI), continuous NRI value, and the integrated discrimination improvement (IDI) showed that the nomogram exhibited superior predictive performance compared to the Sokal, EUTOS, Euro, and ELTS scores (P < 0.05). In addition, the clinical decision curve analysis (DCA) showed that the nomogram was useful for clinical decision-making. In predicting treatment response, only Sokal and CML-IMP risk stratification can effectively predict the cumulative acquisition rates of CCyR, MMR, and DMR (P<0.05). Conclusion: We constructed a nomogram that can be effectively used to predict the efficacy of imatinib in patients with newly diagnosed CML-CP based on a single center, 10-year retrospective cohort study.

Engineering Escherichia coli to Efficiently Produce Colanic Acid with Low Molecular Mass and Viscosity.

Colanic acid (CA) is exopolysaccharide that presents growing potential in the food and healthcare industry as a versatile polymer. Previously, we have constructed the Escherichia coli strain WWM16 which can efficiently produce CA. In this study, WWM16 has been further engineered to produce a higher yield of CA with low molecular mass and viscosity. The gene mcbR encoding a transcriptional factor, and the genes opgD, opgG, and opgH related to the biosynthesis of osmoregulated periplasmic glucans were deleted in E. coli WWM16, and the resulting strain WWM166 produced 18.1 g/L CA. The expression level of wcaD encoding the polymerase in WWM166 was downregulated using CRISPRi. As a result, the strain WWM166/pWpD1 could produce 49.9 g/L CA with lower molecular mass. CA products were purified from both WWM166 and WWM166/pWpD1, and their molecular mass, viscosity, fluidity, hygroscopicity, and antioxidant activity were determined and compared. These findings demonstrate the potential application of CA with different molecular masses to prolong life and protect skin in the food and cosmetic industries.

Real biofuel and fossil-fuel soot combustion activities in active and passive regeneration of diesel/gasoline particulate filters under different O2/NOx concentrations.

In this work, we aim to investigate and compare the combustion reactivities of real biofuel soot and fossil-fuel soot in the active and passive regeneration conditions of DPF and GPF through temperature-programmed oxidation (TPO). Higher reactivity of biofuel soot is achieved even under GPF conditions with extremely low oxygen concentration (~ 1%), which provides a great potential for low-temperature regeneration of GPF. Such a result is mainly attributed to the low graphitization and less surface C = C groups of biofuel soot. Unfortunately, the presence of high-content ashes (~ 47%) and P impurity in real biofuel soot hinder its combustion reactivity. TPO evidences that the O2/NOX-lacking conditions in GPF are key factors to impact the combustion of soot, especially fossil-fuel soot. This work provides some useful information for understanding real biofuel and fossil-fuel soot combustion in GPF and DPF regeneration and further improvement in filter regeneration process.

Prior to ABOi liver transplant with PD-1 inhibitor in patients with hepatocellular carcinoma: A case report.

BACKGROUND: Liver transplantation (LT) is a unique and effective method for treating end-stage liver diseases and acute liver failure, bringing hope to many patients with liver cancer. LT is currently widely used in the treatment of liver diseases. However, there have been no patients with liver cancer who have undergone ABO-incompatible (ABOi) LT after treatment with the programmed cell death protein 1 (PD-1) inhibitor reported in the literature. CASE PRESENTATION: A patient with liver cancer who received sintilimab injection, an anti-PD1 therapy, before LT was admitted in the transplantation centre. This patient underwent ABOi LT. The perioperative treatment strategy of this patient was reported. A desensitisation protocol was conducted urgently for the patient before operation, and the immunosuppression programme of LT was adjusted. After operation, isoagglutinin titer and liver function indicators were strictly monitored. The patient recovered well after operation, and no sign of rejection reaction was observed. CONCLUSION: We reported a patient with hepatocellular carcinoma (HCC) who received PD-1 inhibitor treatment before operation and successfully underwent ABOi LT. The present case report provides novel insights into the perioperative management of utilizing PD-1 inhibitors prior to ABOi LT in patients diagnosed with hepatocellular carcinoma (HCC).

Magnetic Field-induced Disordered Phase of Spinel Oxides for High Battery Performance.

The disordered phase of spinel LiMn1.5Ni0.5O4 (LNMO) is more appealing as high-voltage cathode due to its superior electrochemical performance compared to its ordered counterpart. Various methods are developed to induce a phase transition. However, the resulting materials often suffer from capacity degradation due to the adverse influence of accompanying Mn3+ ions. This study presents the utilization of local magnetic fields generated by a magnetic Fe3O4 shell to induce a disordered phase transition in LNMO at lower temperature, transitioning it from an order state without significantly increasing the Mn3+ content. The pivotal role played by the local magnetic fields is evidenced through comparisons with samples with nonmagnetic Al2O3 shell, samples subjected to sole heat treatment, and samples heat-treated within magnetic fields. The key finding is that magnetic fields can initiate a radical pair mechanism, enabling the induction of order-disorder phase transition even at lower temperatures. The disordered spinal LNMO with a magnetic Fe3O4 shell exhibits excellent cycling stability and kinetic properties in electrochemical characterization as a result. This innovation not only unravels the intricate interplay between the disordered phase and Mn3+ content in the cathode spinel but also pioneers the use of magnetic field effects for manipulating material phases.

Predicting the Population Risk of Suicide Using Routinely Collected Health Administrative Data in Quebec, Canada: Model-Based Synthetic Estimation Study.

BACKGROUND: Suicide is a significant public health issue. Many risk prediction tools have been developed to estimate an individual's risk of suicide. Risk prediction models can go beyond individual risk assessment; one important application of risk prediction models is population health planning. Suicide is a result of the interaction among the risk and protective factors at the individual, health care system, and community levels. Thus, policy and decision makers can play an important role in suicide prevention. However, few prediction models for the population risk of suicide have been developed. OBJECTIVE: This study aims to develop and validate prediction models for the population risk of suicide using health administrative data, considering individual-, health system-, and community-level predictors. METHODS: We used a case-control study design to develop sex-specific risk prediction models for suicide, using the health administrative data in Quebec, Canada. The training data included all suicide cases (n=8899) that occurred from January 1, 2002, to December 31, 2010. The control group was a 1% random sample of living individuals in each year between January 1, 2002, and December 31, 2010 (n=645,590). Logistic regression was used to develop the prediction models based on individual-, health care system-, and community-level predictors. The developed model was converted into synthetic estimation models, which concerted the individual-level predictors into community-level predictors. The synthetic estimation models were directly applied to the validation data from January 1, 2011, to December 31, 2019. We assessed the performance of the synthetic estimation models with four indicators: the agreement between predicted and observed proportions of suicide, mean average error, root mean square error, and the proportion of correctly identified high-risk regions. RESULTS: The sex-specific models based on individual data had good discrimination (male model: C=0.79; female model: C=0.85) and calibration (Brier score for male model 0.01; Brier score for female model 0.005). With the regression-based synthetic models applied in the validation data, the absolute differences between the synthetic risk estimates and observed suicide risk ranged from 0% to 0.001%. The root mean square errors were under 0.2. The synthetic estimation model for males correctly predicted 4 of 5 high-risk regions in 8 years, and the model for females correctly predicted 4 of 5 high-risk regions in 5 years. CONCLUSIONS: Using linked health administrative databases, this study demonstrated the feasibility and the validity of developing prediction models for the population risk of suicide, incorporating individual-, health system-, and community-level variables. Synthetic estimation models built on routinely collected health administrative data can accurately predict the population risk of suicide. This effort can be enhanced by timely access to other critical information at the population level.

The relationship between coffee-related factors and cortical and hippocampal structure: a triangulation of evidence approach and Mendelian randomization research.

Objective: Existing studies have reported sustained changes in the cortical structure of rats due to coffee-related factors, which are speculated to occur in the human body. However, there is a lack of research on this topic. Additionally, previous observational studies have found the impact of diseases on cortical structure and the potential therapeutic effects of coffee on these diseases. Our aim was to study the causal effects of coffee-related factors on the human brain using SNPs (single nucleotide polymorphisms). We will connect these discovered causal effects to the impact of diseases on the brain. Through triangulating evidence, we will reveal the potential active areas of coffee in preventing diseases. Methods: We utilized GWAS data from multiple cohorts and their databases, selecting instrumental variables for genetic prediction of coffee intake and plasma levels of caffeine and its direct metabolites. We applied these instrumental variables to individual data on cortical thickness and surface area, as well as hippocampal volume, from the ENIGMA and CHARGE consortium for Mendelian randomization analysis (MR). Triangular evidence was obtained by integrating existing evidence through a specified retrieval strategy, calculating the overlap between coffee's effects on brain regions and disease-related brain regions to identify potential regions of action. Results: The MR analysis yielded 93 positive results for 9 exposures, among which theobromine, a metabolite in the caffeine pathway, was found to be associated with increased hippocampal volume. For cortical structure, theobromine in the caffeine pathway was associated with a decrease in total surface area, while theobromine and caffeine in the pathway were associated with an increase in total thickness. The overlap rate of triangular evidence showed no difference in both overall and subgroup analyses, indicating a high overlap between the effects of coffee on brain regions and disease. Conclusions: From predicted outcomes from causal effects, coffee intake-related factors may have lasting effects on cortical structure. Additionally, theobromine and theophylline have the greatest impact on certain brain gyri, rather than caffeine. Triangulation evidence indicates that disease and coffee intake-related factors act on the same cortical regions, suggesting the presence of potential shared or antagonistic pathways.

Adhesion between EVs and tumor cells facilitated EV-encapsulated doxorubicin delivery via ICAM1.

Doxorubicin (Dox) is an anti-tumor drug with a broad spectrum, whereas the cardiotoxicity limits its further application. In clinical settings, liposome delivery vehicles are used to reduce Dox cardiotoxicity. Here, we substitute extracellular vesicles (EVs) for liposomes and deeply investigate the mechanism for EV-encapsulated Dox delivery. The results demonstrate that EVs dramatically increase import efficiency and anti-tumor effects of Dox in vitro and in vivo, and the efficiency increase benefits from its unique entry pattern. Dox-loading EVs repeat a "kiss-and-run" motion before EVs internalization. Once EVs touch the cell membrane, Dox disassociates from EVs and directly enters the cytoplasm, leading to higher and faster Dox import than single Dox. This unique entry pattern makes the adhesion between EVs and cell membrane rather than the total amount of EV internalization the key factor for regulating the Dox import. Furthermore, we recognize ICAM1 as the molecule mediating the adhesion between EVs and cell membranes. Interestingly, EV-encapsulated Dox can induce ICAM1 expression by irritating IFN-γ and TNF-α secretion in TME, thereby increasing tumor targeting of Dox-loading EVs. Altogether, EVs and EV-encapsulated Dox synergize via ICAM1, which collectively enhances the curative effects for tumor treatment.

The prognostic impact of tumor location in non-muscle-invasive bladder cancer patients undergoing transurethral resection: insights from a cohort study utilizing chinese multicenter and SEER registries.

OBJECTIVE: Most bladder cancers are non-muscle invasive bladder cancer (NMIBC), and transurethral resection of bladder tumors (TURBT) is the standard treatment. However, postoperative recurrence remains a significant challenge, and the influence of bladder tumor location on prognosis is still unclear. This study aims to investigate how tumor location affects the prognosis of NMIBC patients undergoing TURBT and to identify the optimal surgical approach. METHODS: A multicenter study was conducted, which included Chinese NMIBC data from 15 hospitals (1996-2019) and data from 17 registries of the Surveillance, Epidemiology, and End Results database (SEER) (2000-2020). Patients initially diagnosed with NMIBC and undergoing TURBT or partial cystectomy were analyzed, with cases lost to follow-up or with missing data excluded. The study investigated the overall survival (OS), disease-specific survival (DSS), and recurrence-free survival (RFS) among patients with different tumor locations. Kaplan-Meier, Cox regression, and propensity score matching methods were employed to explore the association between tumor location and prognosis. Stratified populations were analyzed to minimize bias. RESULTS: This study included 118,477 NMIBC patients and highlighted tumor location as a crucial factor impacting post-TURBT prognosis. Both anterior wall and dome tumors independently predicted adverse outcomes in two cohorts. For anterior wall tumors, the Chinese cohort showed hazard ratios (HR) for OS of 4.35 (P < 0.0001); RFS of 2.21 (P < 0.0001); SEER cohort OS HR of 1.10 (P = 0.0001); DSS HR of 1.13 (P = 0.0183). Dome tumors displayed similar trends (Chinese NMIBC cohort OS HR of 7.91 (P < 0.0001); RFS HR of 2.12 (P < 0.0001); SEER OS HR of 1.05 (P = 0.0087); DSS HR of 1.14 (P = 0.0006)). Partial cystectomy significantly improved the survival of dome tumor patients compared to standard TURBT treatment (P < 0.01). CONCLUSION: This study reveals the significant impact of tumor location in NMIBC patients on the outcomes of TURBT treatment, with tumors in the anterior wall and bladder dome showing poor post-TURBT prognosis. Compared to TURBT treatment, partial cystectomy improves the prognosis for bladder dome tumors. This study provides guidance for personalized treatment and prognosis management for NMIBC patients.

Characterization of a secondary hydroxy-acyltransferase for lipid A in Vibrio parahaemolyticus.

Lipid A plays a crucial role in Vibrio parahaemolyticus. Previously we have reported the diversity of secondary acylation of lipid A in V. parahaemolyticus and four V. parahaemolyticus genes VP_RS08405, VP_RS01045, VP_RS12170, and VP_RS00880 exhibiting homology to the secondary acyltransferases in Escherichia coli. In this study, the gene VP_RS12170 was identified as a specific lipid A secondary hydroxy-acyltransferase responsible for transferring a 3-hydroxymyristate to the 2'-position of lipid A. Four E. coli mutant strains WHL00, WHM00, WH300, and WH001 were constructed, and they would synthesize lipid A with different structures due to the absence of genes encoding lipid A secondary acyltransferases or Kdo transferase. Then V. parahaemolyticus VP_RS12170 was overexpressed in W3110, WHL00, WHM00, WH300, and WH001, and lipid A was isolated from these strains and analyzed by using thin-layer chromatography and high-performance liquid chromatography-tandem mass spectrometry. The detailed structural changes of lipid A in these mutant strains with and without VP_RS12170 overexpression were compared and conclude that VP_RS12170 can specifically transfer a 3-hydroxymyristate to the 2'-position of lipid A. This study also demonstrated that the function of VP_RS12170 is Kdo-dependent and its favorite substrate is Kdo-lipid IVA. These findings give us better understanding the biosynthetic pathway and the structural diversity of V. parahaemolyticus lipid A.

Microbial chassis design and engineering for production of gamma-aminobutyric acid.

Gamma-aminobutyric acid (GABA) is a non-protein amino acid which is widely applied in agriculture and pharmaceutical additive industries. GABA is synthesized from glutamate through irreversible α-decarboxylation by glutamate decarboxylase. Recently, microbial synthesis has become an inevitable trend to produce GABA due to its sustainable characteristics. Therefore, reasonable microbial platform design and metabolic engineering strategies for improving production of GABA are arousing a considerable attraction. The strategies concentrate on microbial platform optimization, fermentation process optimization, rational metabolic engineering as key metabolic pathway modification, promoter optimization, site-directed mutagenesis, modular transporter engineering, and dynamic switch systems application. In this review, the microbial producers for GABA were summarized, including lactic acid bacteria, Corynebacterium glutamicum, and Escherichia coli, as well as the efficient strategies for optimizing them to improve the production of GABA.

Population Structures and Dynamics of Rhododendron Communities with Different Stages of Succession in Northwest Guizhou, China.

To explore the population structures and dynamics of Rhododendron shrub communities at different stages of succession in northwest Guizhou, China, this study examined the populations of Rhododendron annae and Rhododendron irroratum shrub with two different stages. A space-for-time substitution was employed to establish the diameter class/height structures, static life tables, and survival/mortality rate/disappearance rate curves of both Rhododendron populations with different orders of succession. Their structural and quantitative dynamics were analyzed, and their development trends were predicted. The results showed that, quantitatively, the populations of R. annae and R. irroratum in the two Rhododendron communities with different orders of succession were dominated by age classes one, two, and three as well as height classes i, ii, and iii. The number of Rhododendron plants at the three age classes and the three height classes accounted for 97.61-100% of the total. The quantitative dynamic indices of R. annae and R. irroratum were both greater than 0, with and without considering external interference. In terms of age class and height structures, both Rhododendron populations were expanding populations, presenting "inverted-J-shaped" and irregular pyramid patterns. There was a sufficient number of young individuals, but few or no old individuals. Both survival curves of the populations of R. annae and R. irroratum in the two Rhododendron communities with different orders of succession belonged to the Deevy-II type. In the late stage of succession, the mortality curves and disappearance curves of both Rhododendron populations in these communities presented a trend of increasing first and then decreasing with increasing age class. This result indicates that at each age class, R. annae and R. irroratum showed a trend of gradual increase after two, four, and six years. In brief, the populations of R. annae and R. irroratum have rich reserves of seedlings and saplings, but high mortality and disappearance rates. In this context, it is necessary to reduce human interference and implement targeted conservation measures to promote the natural renewal of Rhododendron populations.

TEMPO-Grafted Polystyrene/Polymethacrylate Organosiloxane Janus Nanohybrids as Efficient Pickering Interfacial Catalyst for Selective Aerobic Oxidation of Cinnamyl Alcohol.

The novel 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) groups immobilized on functional polymers or nanoparticles emerged as potential Pickering interfacial catalysts (PICs) for effective catalysis in biphasic systems. In this study, a snowman-shaped Janus-structured polymer with TEMPO-anchored nanohybrid particles (SM-JPP-TEMPO) was prepared and employed as a potential PIC in the Anelli-Montanari system for the selective oxidation of alcohol. The amphiphilic character of SM-JPP-TEMPO particles plays a dual role as an emulsifier and catalyst in the Pickering emulsion. As a result, it enables smaller droplets (102 µm) at the water-in-oil (W/O) interface and reduces the interfacial tension from 26.58 to 17.38 mN/m, which improves the stability of the Pickering emulsion system. This constructed Pickering emulsion microreactor offers a larger interface contact area and shortens the mass transfer distance of the substrate of cinnamyl alcohol, which significantly enhances the catalytic conversion at the Anelli-Montanari oxidation system, thus achieving remarkable conversion efficiency of (92.3%) with excellent selectivity (99%) in static (stirring-free) condition. It was found that the Janus nanohybrid catalyst (SM-JPP-TEMPO) enhanced 1.29-fold catalytic efficiency compared to the TEMPO grafted spherical polystyrene nanoparticle (PS-NPs-TEMPO) catalyst (72%). Moreover, after seven consecutive cycles, the Janus nanocatalyst (SM-JPP-TEMPO) maintained the conversion significantly. Hence, these results collectively highlight that the amphiphilic SM-JPP-TEMPO catalyst provides an efficient and eco-friendly strategy for the intensification of liquid-liquid biphasic reaction systems for potential applications in industries.

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec.

Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. Artificial intelligence (AI) and machine learning (ML) have emerged to harness large-scale datasets to enhance risk detection. In order to trust and act upon the predictions made with ML, more intuitive user interfaces must be validated. Thus, Interpretable AI is one of the crucial directions which could allow policy and decision makers to make reasonable and data-driven decisions that can ultimately lead to better mental health services planning and suicide prevention. This research aimed to develop sex-specific ML models for predicting the population risk of suicide and to interpret the models. Data were from the Quebec Integrated Chronic Disease Surveillance System (QICDSS), covering up to 98% of the population in the province of Quebec and containing data for over 20,000 suicides between 2002 and 2019. We employed a case-control study design. Individuals were considered cases if they were aged 15+ and had died from suicide between January 1st, 2002, and December 31st, 2019 (n = 18339). Controls were a random sample of 1% of the Quebec population aged 15+ of each year, who were alive on December 31st of each year, from 2002 to 2019 (n = 1,307,370). We included 103 features, including individual, programmatic, systemic, and community factors, measured up to five years prior to the suicide events. We trained and then validated the sex-specific predictive risk model using supervised ML algorithms, including Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Multilayer perceptron (MLP). We computed operating characteristics, including sensitivity, specificity, and Positive Predictive Value (PPV). We then generated receiver operating characteristic (ROC) curves to predict suicides and calibration measures. For interpretability, Shapley Additive Explanations (SHAP) was used with the global explanation to determine how much the input features contribute to the models' output and the largest absolute coefficients. The best sensitivity was 0.38 with logistic regression for males and 0.47 with MLP for females; the XGBoost Classifier with 0.25 for males and 0.19 for females had the best precision (PPV). This study demonstrated the useful potential of explainable AI models as tools for decision-making and population-level suicide prevention actions. The ML models included individual, programmatic, systemic, and community levels variables available routinely to decision makers and planners in a public managed care system. Caution shall be exercised in the interpretation of variables associated in a predictive model since they are not causal, and other designs are required to establish the value of individual treatments. The next steps are to produce an intuitive user interface for decision makers, planners and other stakeholders like clinicians or representatives of families and people with live experience of suicidal behaviors or death by suicide. For example, how variations in the quality of local area primary care programs for depression or substance use disorders or increased in regional mental health and addiction budgets would lower suicide rates.

Method of generating speckle patterns for digital image correlation based on modified Conway's Game of Life.

The measurement accuracy of digital image correlation (DIC) is influenced by the quality of the speckle pattern. Although various models for generating random speckle patterns have been well discussed, obtaining appropriate speckle images with isotropic quality and performance could be a challenging issue in DIC. In this paper, we propose a novel (to our knowledge) method for generating speckle patterns based on modified Conway's game of life (GoL). By sequentially assembling the speckle patterns generated from the modified GoL, we produced the GoL speckle image. Then, verification and comparison experiments were conducted through pure in-plane translations. The results show that the generated speckle image which was resized with k s=6& k r=2 processing and subsequently fuzzified using a Gaussian filter, produces the best accuracy for DIC measurement. Furthermore, based on the rigid body in-plane rotation displacement tests in the physical experimental results of three different speckle images, the GoL speckle generated from our proposed method shows the smallest measurement error. This indicates that the proposed speckle patterns generating method could provide a new type of speckle pattern with better quality and accuracy.

Highly luminescent and stable CsPbBr3 perovskite nanocrystals coated with polyethersulfone for white light-emitting diode applications.

Simultaneously improving the stability and photoluminescence quantum yield (PLQY) of all inorganic perovskite nanocrystals (NCs) is crucial for their practical utilization in various optoelectronic devices. Here, CsPbBr3 NCs coated with polyethersulfone (PES) were prepared via an in-situ co-precipitation method. The sulfone groups in PES bind to undercoordinated lead ion (Pb2+) on the CsPbBr3 NCs, resulting in significant reduction of surface defects, thus enhancing the PLQY from 74.2% to 88.3%. Meanwhile, the PES-coated NCs exhibit high water resistance and excellent heat and light stability, maintaining over 85% of the initial PL intensity under thermal aging (70°C, 4 h) and continuous 365 nm ultraviolet (UV) light irradiation (24 W, 8 h) conditions. By contrast, the PL intensity of the control NCs dramatically dropped to less than 40%. Finally, a diode emitting bright white light was fabricated utilizing the PES-coated CsPbBr3 NCs, which exhibits a color gamut of ~110% NTSC standard.

Daytime HyWFS approach for daylight adaptive optics wavefront sensing.

Bright daylight photon noise and the saturation of wavefront sensors pose challenges to high-resolution daytime imaging. In this paper, a daytime hybrid wavefront sensor (HyWFS) approach for real-time wavefront sensing in daylight adaptive optics (AO) is described. The Shack-Hartmann wavefront sensor (SHWFS) algorithm is used to efficiently compensate large-scale wavefronts, while the pyramid wavefront sensor (PyWFS) algorithm offers highly sensitive correction of small wavefronts. Daylight closed-loop AO experiments were performed using the daytime HyWFS approach with both algorithms, respectively. The experiment results indicate that the proposed approach provides accurate daylight AO correction and allows for a simple switch between the two algorithms without increasing system complexity. The daytime HyWFS approach can serve as an alternative for daylight natural guide star AO, enabling high-resolution observation of resident space objects no longer limited to dawn and dusk.

BATF promotes extramedullary infiltration through TGF-ß1/Smad/MMPs axis in acute myeloid leukemia.

Acute myeloid leukemia (AML) is one of the most prevalent types of leukemia and is challenging to cure for most patients. Basic Leucine Zipper ATF-Like Transcription Factor (BATF) has been reported to participate in the development and progression of numerous tumors. However, its role in AML is largely unknown. In this study, the expression and prognostic value of BATF were examined in AML. Our results demonstrated that BATF expression was upregulated in AML patients, which was significantly correlated with poor clinical characteristics and survival. Afterward, functional experiments were performed after knocking down or overexpressing BATF by transfecting small interfering RNAs and overexpression plasmids into AML cells. Our findings revealed that BATF promoted the migratory and invasive abilities of AML cells in vitro and in vivo. Moreover, the target genes of BATF were searched from databases to explore the binding of BATF to the target gene using ChIP and luciferase assays. Notably, our observations validated that BATF is bound to the promoter region of TGF-ß1, which could transcriptionally enhance the expression of TGF-ß1 and activate the TGF-ß1/Smad/MMPs signaling pathway. In summary, our study established the aberrantly high expression of BATF and its pro-migratory function via the TGF-ß1-Smad2/3-MMP2/9 axis in AML, which provides novel insights into extramedullary infiltration of AML.

A cross-sectional study of the relationship between frequency of cannabis use and psychiatric symptoms among people seeking mental health and addiction services in Nova Scotia (2019-21).

BACKGROUND: Cannabis use may be a modifiable risk factor for mental health problems; however, the role of cannabis use frequency in population seeking mental health and addiction services remains unclear. This study aimed to: 1) compare the prevalence and functional impact of psychiatric symptoms among frequent, infrequent, and non-users of cannabis; and 2) evaluate the associations between cannabis use frequency and functional impact of psychiatric symptoms in help-seeking individuals. METHODS: Data from the Mental Health and Addictions (MHA) Central Intake system in Nova Scotia, Canada was used. Participants aged 19-64 who received MHA Intake assessments from September 2019 to December 2021 with complete information about substance use were included (N = 20,611). Cannabis use frequency over past 30 days was categorized into frequent (>4 times a month), infrequent (≤4 times a month), and non-use. Psychiatric symptomatology consists of five domains: mood, anxiety, psychosis, cognition, and externalizing behaviors. Multivariate ordinal logistic regression was used to examine the associations between cannabis use frequency and functional impact of psychiatric symptoms. RESULTS: Frequent and infrequent cannabis users had a higher prevalence of psychiatric symptoms in each domain than non-users, while no significant differences were found between frequent and infrequent users. Frequent cannabis use was associated with greater functional impact of psychiatric symptoms in each domain compared to non-users, while infrequent use was only associated with greater functional impact of externalizing behaviors. CONCLUSION: Frequent cannabis use is associated with increased prevalence and functional impact of psychiatric symptoms among adults seeking mental health services.

Proton pump inhibitors enhance macropinocytosis-mediated extracellular vesicle endocytosis by inducing membrane v-ATPase assembly.

Besides participating in diverse pathological and physiological processes, extracellular vesicles (EVs) are also excellent drug-delivery vehicles. However, clinical drugs modulating EV levels are still lacking. Here, we show that proton pump inhibitors (PPIs) reduce EVs by enhancing macropinocytosis-mediated EV uptake. PPIs accelerate intestinal cell endocytosis of autocrine immunosuppressive EVs through macropinocytosis, thereby aggravating inflammatory bowel disease. PPI-induced macropinocytosis facilitates the clearance of immunosuppressive EVs from tumour cells, improving antitumor immunity. PPI-induced macropinocytosis also increases doxorubicin and antisense oligonucleotides of microRNA-155 delivery efficiency by EVs, leading to enhanced therapeutic effects of drug-loaded EVs on tumours and acute liver failure. Mechanistically, PPIs reduce cytosolic pH, promote ATP6V1A (v-ATPase subunit) disassembly from the vacuolar membrane and enhance the assembly of plasma membrane v-ATPases, thereby inducing macropinocytosis. Altogether, our results reveal a mechanism for macropinocytic regulation and PPIs as potential modulators of EV levels, thus regulating their functions.