Discordance between Remnant Cholesterol and Low-density Lipoprotein Cholesterol Predicts Cardiovascular Disease: the Kailuan Prospective Cohort Study.

BACKGROUND: Previous studies have shown that remnant cholesterol (RC) was associated with cardiovascular disease (CVD). The study aim to identify the association of RC and the discordance between RC and lipoprotein cholesterol (LDL-C) with CVD. METHODS: Data was obtained from the Kailuan study. RC was calculated as the non high-density lipoprotein cholesterol minus LDL-C. Discordant RC and LDL-C were defined by percentile difference and clinical cutoff points. Cox proportional hazard models were used to explore the association of RC and the discordance between RC and LDL-C with CVD. RESULTS: Total of 96,769 participants were inclued, with the median age of 51.61 years, 79.56% of male. There was a significant association between RC levels and the risk of CVD, with an HR of 1.10 (95% CI, 1.08-1.13) in the continuous analysis. The discordantly high RC group had a significant increase in CVD, MI, and stroke risk, with HRs of 1.18 (95%CI, 1.10-1.26), 1.23 (1.06-1.43), and 1.15 (1.07-1.24), respectively. Compared to the group with low LDL-C and low RC, the group with low LDL-C and high RC had significantly higher incidences of CVD (HR, 1.33 [95% CI, 1.26-1.40]), MI (HR, 1.59 [95% CI, 1.41-1.80]), and stroke (HR, 1.28 [95% CI, 1.20-1.35]). CONCLUSIONS: Elevated levels of RC and discordantly high RC with LDL-C both were associated with the risk of CVD, MI, and stroke. These findings demonstrate the clinical significance of identifying residual risk related to RC.

Prognostic Value of a Multi-mRNA Signature for 1-Year All-Cause Death in Hospitalized Patients With Heart Failure With a Preserved Ejection Fraction.

BACKGROUND: Heart failure with preserved ejection fraction is a major global public health problem, while effective risk stratification tools are still lacking. We sought to construct a multi-mRNA signature to predict 1-year all-cause death. METHODS: We selected 30 patients with heart failure with preserved ejection fraction who died during 1-year follow-up and 30 who survived in the discovery set. One hundred seventy-one and 120 patients with heart failure with preserved ejection fraction were randomly selected as a test set and a validation set, respectively. We performed mRNA microarrays in all patients. RESULTS: We constructed a 5-mRNA signature for predicting 1-year all-cause death. The scores of the 5-mRNA signature were significantly associated with the 1-year risk of all-cause death in both the test set (hazard ratio, 2.72 [95% CI, 1.98-3.74]; P<0.001) and the validation set (hazard ratio, 3.95 [95% CI, 2.40-6.48]; P<0.001). Compared with a reference model, which included sex, ASCEND-HF (Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure) score, history of HF and NT-proBNP (N-terminal pro-B-type natriuretic peptide), the 5-mRNA signature had a better discrimination capability, with an increased area under the curve from 0.696 to 0.813 in the test set and from 0.712 to 0.848 in the validation set. A composite model integrating the 5-mRNA risk score and variables in the reference model demonstrated an excellent discrimination capability, with an area under the curve of 0.861 (95% CI, 0.784-0.939) in the test set and an area under the curve of 0.859 (95% CI, 0.755-0.963) in the validation set. The net reclassification improvement and integrated discrimination improvement indicated that the composite model significantly improved patient classification compared with the reference model in both sets (P<0.001). CONCLUSIONS: The 5-mRNA signature is a promising predictive tool for 1-year all-cause death and shows improved prognostic power over the established risk scores and NT-proBNP in patients with heart failure with preserved ejection fraction.

Second victim experiences and impact among acute care nurses: An exploratory study.

AIM: To explore the experience of second victim symptoms and adverse outcomes among nurses working in public healthcare institutions; understand the preferred components of a structured support programme; and explore the barriers to accessing existing support strategies. BACKGROUND: The second victim phenomenon is experienced by nurses during patient-related adverse events, requiring further exploration. METHODS: A mixed-methods design. Second Victim Experience and Support Tool and semi-structured individual interviews were used among nurses involved in adverse events that occurred from January 2022 to April 2023. Descriptive statistics was used to describe sociodemographic characteristics and survey responses. Thematic analysis was used to analyse qualitative data. RESULTS: Nurses (n = 12) experienced second victim-related physical, psychological and professional distress (58.3% to 83.3%) within one month after the event. Nurses continued to experience second victim-related distress (58.3%) three months after and turnover intentions (58.4%). Having a respected peer to discuss what happened was the most desired component of a support programme (75.0%). Five qualitative themes: (i) whirlwind of immediate emotions, (ii) lasting impact of adverse events, (iii) organisational barriers, (iv) coping resources at organisational level and (v) positive individual coping strategies. DISCUSSION: Nurses experienced immediate and profound distress, highlighting the pervasive and distressing nature of the second victim phenomenon. CONCLUSION: It is critical to recognise the second victim phenomenon and improve organisational climate to provide adequate support to affected nurses. IMPLICATIONS FOR NURSING AND HEALTH POLICY: Organisations can establish a structured second victim support system, allowing nurses to seek emotional aid during the occurrence of adverse events. Establishing national policies as guidelines for organisations to refer to, raise awareness of the second victim phenomenon, and provide a standardised approach for identification and intervention for affected nurses.

The mediating role of trait impulsivity in the relation between cue-induced craving and functional connectivity within the salience network among abstinent patients with methamphetamine use disorder.

Given the widespread use and relapse of methamphetamine (METH), it has caused serious public health burdens globally. However, the neurobiological basis of METH addiction remains poorly understood. Therefore, this study aimed to use magnetic resonance imaging (MRI) to investigate changes in brain networks and their connection to impulsivity and drug craving in abstinent individuals with METH use disorder (MUDs). A total of 110 MUDs and 55 age- and gender-matched healthy controls (HCs) underwent resting-state functional MRI and T1-weighted imaging scans, and completed impulsivity and cue-induced craving measurements. We applied independent component analysis to construct functional brain networks and multivariate analysis of covariance to investigate group differences in network connectivity. Mediation analyses were conducted to explore the relationships among brain-network functional connectivity (FC), impulsivity, and drug craving in the patients. MUDs showed increased connectivity in the salience network (SN) and decreased connectivity in the default mode network compared to HCs. Impulsivity was positively correlated with FC within the SN and played a completely mediating role between METH craving and FC within the SN in MUDs. These findings suggest alterations in functional brain networks underlying METH dependence, with SN potentially acting as a core neural substrate for impulse control disorders.

Unsupervised stain augmentation enhanced glomerular instance segmentation on pathology images.

PURPOSE: In pathology images, different stains highlight different glomerular structures, so a supervised deep learning-based glomerular instance segmentation model trained on individual stains performs poorly on other stains. However, it is difficult to obtain a training set with multiple stains because the labeling of pathology images is very time-consuming and tedious. Therefore, in this paper, we proposed an unsupervised stain augmentation-based method for segmentation of glomerular instances. METHODS: In this study, we successfully realized the conversion between different staining methods such as PAS, MT and PASM by contrastive unpaired translation (CUT), thus improving the staining diversity of the training set. Moreover, we replaced the backbone of mask R-CNN with swin transformer to further improve the efficiency of feature extraction and thus achieve better performance in instance segmentation task. RESULTS: To validate the method presented in this paper, we constructed a dataset from 216 WSIs of the three stains in this study. After conducting in-depth experiments, we verified that the instance segmentation method based on stain augmentation outperforms existing methods across all metrics for PAS, PASM, and MT stains. Furthermore, ablation experiments are performed in this paper to further demonstrate the effectiveness of the proposed module. CONCLUSION: This study successfully demonstrated the potential of unsupervised stain augmentation to improve glomerular segmentation in pathology analysis. Future research could extend this approach to other complex segmentation tasks in the pathology image domain to further explore the potential of applying stain augmentation techniques in different domains of pathology image analysis.

Postoperative Nausea and Vomiting in Female Patients Undergoing Laparoscopic Gastrointestinal Surgery with Double Prophylactic Therapy.

Purpose Postoperative nausea and vomiting (PONV) is a major problem after surgery. This study aimed to demonstrate the incidence of PONV and the potential associated factors in female patients undergoing laparoscopic gastrointestinal surgery against the background of double prophylactic therapy. Methods Our retrospective study recruited 109 female patients undergoing laparoscopic gastrointestinal surgery with double prophylactic therapy, combining palonosetron with dexamethasone, from October 2020 to March 2021, at the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China. Patient characteristics and perioperative management factors were included in univariate and multivariate analyses to identify factors influencing PONV. Results Four patients lacked complete records, and of the 105 patients included in the final analysis, 53 (50.5%) patients developed PONV. Two influencing factors for PONV were identified: a history of chemotherapy (odds ratio [OR] 0.325, 95% confidence interval [CI] 0.123-0.856; p = 0.023) and dosage of hydromorphone ≥ 0.02 mg/kg (OR 2.857, 95% CI 1.247-6.550; p = 0.013). The performance of the multivariate logistic regression was evaluated by analyzing receiver operating characteristic curves, resulting in an area under the curve value of 0.673. Conclusion The incidence of PONV remains high in female patients undergoing laparoscopic gastrointestinal surgery, even with double prophylactic therapy. A dosage of hydromorphone ≥ 0.02 mg/kg may increase risk of PONV, whereas a history of chemotherapy might be a protective factor.

Clinicopathological characteristics and prognosis of synchronous brain metastases from non-small cell lung cancer compared with metachronous brain metastases.

Purpose: Brain metastasis (BM) from non-small cell lung cancer (NSCLC) is a serious complication severely affecting patients' prognoses. We aimed to compare the clinicopathological features and prognosis of synchronous and metachronous BM from NSCLC. Methods: Clinical data of 461 patients with brain metastases from NSCLC who visited the Cancer Hospital of China Medical University from 2005 to 2017 were retrospectively collected. We analyzed the pathophysiological characteristics of synchronous and metachronous BM from NSCLC and survival rates of the patients. Propensity score matching analysis was used to reduce bias between groups. In addition, we used the Kaplan-Meier method for survival analysis, log-rank test to compare survival rates, and Cox proportional hazards regression model for multivariate prognosis analysis. Results: Among 461 patients with BM, the number of people who met the inclusion criteria was 400 cases, and after 1:2 propensity score matching,130 had synchronous BM and 260 had metachronous BM. The survival time was longer for metachronous BM in driver mutation-negative patients with squamous cell carcinoma than synchronous BM. Conversely, metachronous and synchronous BM with gene mutations and adenocarcinoma showed no differences in survival time. Multivariate analysis showed that metachronous BM was an independent prognostic factor for overall survival. Furthermore, the pathological type squamous cell carcinoma and Karnofsky Performance Status score <80 were independent risk factors affecting overall survival. Conclusion: BM status is an independent factor influencing patient outcome. Moreover, synchronous and metachronous BM from NSCLC differ in gene mutation profile, pathological type, and disease progression and hence require different treatments.

Correlation between Corneal Volume and Corneal Biomechanics and Corneal Volume Significance in Staging and Diagnosing Keratoconus.

Purpose: To investigate the relationship between corneal volume (CV) at different zones and corneal biomechanics in keratoconus (KC) along with the significance of CV in diagnosing and staging KC. Methods: This prospective clinical study included 456 keratoconic eyes (Group B) and 198 normal eyes (Group A). Using the topographic KC classification method, Group B was divided into subgroups based on severity (mild, moderate, and severe). The CVs of the 3 mm, 5 mm, and 7 mm zones and biomechanical parameters were obtained by Pentacam and Corvis ST. The diagnostic utility of multirange CVs at different disease stages and severity was determined using a receiver operating characteristic (ROC) curve analysis. Results: The CV of the 7-mm zone had the strongest correlation with A1V, A2T, PD, DA ratio max (2 mm), DA ratio max (1 mm), ARTh, integrated radius, SPA1, and CBI (p < 0.01). The CVs of the Group B subgroups were significantly lower than those of Group A for each diameter range (p < 0.05). There were significant differences between the severe, mild, and moderate subgroups for the 3 mm zone (p < 0.05, all). The 3 mm zone CV exhibited better diagnostic ability in each group for distinguishing KC from the normal cornea (Groups A vs. B: area under the ROC curve (AUC) = 0.926, Groups A vs. B1: AUC = 0.894, Groups A vs. B2: AUC = 0.925, Groups A vs. B3: AUC = 0.953). Conclusion: The CV significantly decreased in keratoconic eyes. Progressive thinning in the 3 mm zone may be a valuable measurement for detecting and staging KC. Combining the CV examination with corneal biomechanical information may effectively enhance the ability to detect KC.

Interfacing data science with cell therapy manufacturing: where we are and where we need to be.

Although several cell-based therapies have received FDA approval, and others are showing promising results, scalable, and quality-driven reproducible manufacturing of therapeutic cells at a lower cost remains challenging. Challenges include starting material and patient variability, limited understanding of manufacturing process parameter effects on quality, complex supply chain logistics, and lack of predictive, well-understood product quality attributes. These issues can manifest as increased production costs, longer production times, greater batch-to-batch variability, and lower overall yield of viable, high-quality cells. The lack of data-driven insights and decision-making in cell manufacturing and delivery is an underlying commonality behind all these problems. Data collection and analytics from discovery, preclinical and clinical research, process development, and product manufacturing have not been sufficiently utilized to develop a "systems" understanding and identify actionable controls. Experience from other industries shows that data science and analytics can drive technological innovations and manufacturing optimization, leading to improved consistency, reduced risk, and lower cost. The cell therapy manufacturing industry will benefit from implementing data science tools, such as data-driven modeling, data management and mining, AI, and machine learning. The integration of data-driven predictive capabilities into cell therapy manufacturing, such as predicting product quality and clinical outcomes based on manufacturing data, or ensuring robustness and reliability using data-driven supply-chain modeling could enable more precise and efficient production processes and lead to better patient access and outcomes. In this review, we introduce some of the relevant computational and data science tools and how they are being or can be implemented in the cell therapy manufacturing workflow. We also identify areas where innovative approaches are required to address challenges and opportunities specific to the cell therapy industry. We conclude that interfacing data science throughout a cell therapy product lifecycle, developing data-driven manufacturing workflow, designing better data collection tools and algorithms, using data analytics and AI-based methods to better understand critical quality attributes and critical-process parameters, and training the appropriate workforce will be critical for overcoming current industry and regulatory barriers and accelerating clinical translation.

Qizhu anticancer prescription enhances immunosurveillance of liver cancer cells by regulating p21-dependent secretory phenotypes.

ETHNOPHARMACOLOGICAL RELEVANCE: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide, largely due to the limitations of available therapeutic strategies. The traditional Chinese medicine Qizhu Anticancer Prescription (QZACP) can improve the quality of life and prolong the survival time of patients with HCC. However, the precise mechanisms underlying the anti-cancer properties of QZACP remain unclear. PURPOSE: This study examined the anti-hepatocarcinogenic properties of QZACP, with a specific focus on its influence on the p21-activated secretory phenotype (PASP)-mediated immune surveillance, to elucidate the underlying molecular pathways involved in HCC. MATERIALS AND METHODS: Cell proliferation was measured using the Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine, and clonogenic assays. The cell cycle was evaluated using flow cytometry, and senescence was identified by staining with senescence-associated beta-galactosidase (SA-ß-gal). A primary liver cancer model produced by diethylnitrosamine was established in C57 BL/6 mice to assess the tumor-inhibitory effect of QZACP. The liver's pathological characteristics were examined using hematoxylin and eosin staining. PASP screening was performed using GeneCards, DisGeNet, Online Mendelian Inheritance in Man, and The Cancer Genome Atlas databases. Western blot analysis, enzyme-linked immunosorbent assay (ELISA), immunofluorescence staining, and Transwell migration assays were performed. RESULTS: Serum containing QZACP enhanced p21 expression, triggered cell cycle arrest, accelerated cell senescence, and suppressed cell proliferation in Huh7 and MHCC-97H liver cancer cells. QZACP reduced the quantity and dimensions of liver tumor nodules and enhanced p21 protein expression, SA-ß-Gal staining in tumor lesions, and cytotoxic CD8+ T cell infiltration. Bioinformatic analyses indicated that PASP factors, including hepatocyte growth factor, decorin (DCN), dermatopontin, C-X-C motif chemokine ligand 14 (CXCL14), and Wnt family member 2 (WNT2), play an important role in the development of HCC. In addition, these factors are associated with the presence of natural killer cells and CD8+ T cells within tumors. Western blotting and ELISA confirmed that QZACP increased DCN, CXCL14, and WNT2 levels in tumor tissues and peripheral blood. CONCLUSIONS: QZACP's suppression of HCC progression may involve cell senescence mediated via p21 upregulation, DCN, CXCL14, and WNT2 secretion, and reversal of the immunosuppressive microenvironment. This study provides insights that can be used in the development of new treatment strategies for HCC.

Trends in the burden and determinants of HIV in the Asia-Pacific region (1990-2019): An age-period-cohort analysis of the 2019 Global Burden of Disease Study.

Although the burden of the human immunodeficiency virus (HIV) in the Asia-Pacific region is increasingly severe, comprehensive evidence of the burden of HIV is scarce. We aimed to report the burden of HIV in people aged 15-79 years from 1990 to 2019 using data from the Global Burden of Disease Study (GBD) 2019. We analyzed rates of age-standardized disability-adjusted life years (ASDR), age-standardized mortality (ASMR), and age-standardized incidence (ASIR) in our age-period-cohort analysis by sociodemographic index (SDI). According to HIV reports in 2019 from 29 countries in the Asia-Pacific region, the low SDI group in Papua New Guinea had the highest ASDR, ASMR, and ASIR. From 1990 to 2019, the ASDR, ASIR, and ASMR of persons with acquired immune deficiency syndrome (AIDS) increased in 21 (72%) of the 29 countries in the Asia-Pacific region. During the same period, the disability-adjusted life years (DALYs) of AIDS patients in the low SDI group in the region grew the fastest, particularly in Nepal. The incidence of HIV among individuals aged 20-30 years in the low-middle SDI group was higher than that of those in the other age groups. In 2019, unsafe sex was the main cause of HIV-related ASDR in the region's 29 countries, followed by drug use. The severity of the burden of HIV/AIDS in the Asia-Pacific region is increasing, especially among low SDI groups. Specific public health policies should be formulated based on the socioeconomic development level of each country to alleviate the burden of HIV/AIDS.

The UF-5000 Atyp.C parameter is an independent risk factor for bladder cancer.

Bladder carcinoma (BC) accounts for > 90% of all urothelial cancers. Pathological diagnosis through cytoscopic biopsy is the gold standard, whereas non-invasive diagnostic tools remain lacking. The "Atyp.C" parameter of the Sysmex UF-5000 urine particle analyzer represents the ratio of nucleus to cytoplasm and can be employed to detect urinary atypical cells. The present study examined the association between urinary Atyp.C values and BC risk. This two-center, retrospective case-control study identified clinical primary or newly recurrent BC (study period, 2022-2023; n = 473) cases together with controls with urinary tract infection randomly matched by age and sex (1:1). Urinary sediment differences were compared using non-parametric tests. The correlations between urinary Atyp.C levels and BC grade or infiltration were analyzed using Spearman's rank correlation. The BC risk factor odds ratio of Atyp.C was calculated using conditional logistic regression, and potential confounder effects were adjusted using stepwise logistic regression (LR). Primary risk factors were identified by stratified analysis according to pathological histological diagnosis. The mean value of urinary Atyp.C in BC cases (1.30 ± 3.12) was 8.7 times higher than that in the controls (0.15 ± 0.68; P < 0.001). Urinary Atyp.C values were positively correlated with BC pathological grade and invasion (r = 0.360, P < 0.001; r = 0.367, P < 0.001). Urinary Atyp.C was an independent risk factor for BC and closely related with BC pathological grade and invasion. Elevated urinary Atyp.C values was an independent risk factor for BC. Our findings support the use of Atyp.C as a marker that will potentially aid in the early diagnosis and long-term surveillance of new and recurrent BC cases.

Radiomics Analysis of Quantitative Maps from Synthetic MRI for Predicting Grades and Molecular Subtypes of Diffuse Gliomas.

PURPOSE: To investigate the feasibility of using radiomics analysis of quantitative maps from synthetic MRI to preoperatively predict diffuse glioma grades, isocitrate dehydrogenase (IDH) subtypes, and 1p/19q codeletion status. METHODS: Data from 124 patients with diffuse glioma were used for analysis (n = 87 for training, n = 37 for testing). Quantitative T1, T2, and proton density (PD) maps were obtained using synthetic MRI. Enhancing tumour (ET), non-enhancing tumour and necrosis (NET), and peritumoral edema (PE) regions were segmented followed by manual fine-tuning. Features were extracted using PyRadiomics and then selected using Levene/T, BorutaShap and maximum relevance minimum redundancy algorithms. A support vector machine was adopted for classification. Receiver operating characteristic curve analysis and integrated discrimination improvement analysis were implemented to compare the performance of different radiomics models. RESULTS: Radiomics models constructed using features from multiple tumour subregions (ET + NET + PE) in the combined maps (T1 + T2 + PD) achieved the highest AUC in all three prediction tasks, among which the AUC for differentiating lower-grade and high-grade diffuse gliomas, predicting IDH mutation status and predicting 1p/19q codeletion status were 0.92, 0.95 and 0.86 respectively. Compared with those constructed on individual T1, T2, and PD maps, the discriminant ability of radiomics models constructed on the combined maps separately increased by 11, 17 and 10% in predicting glioma grades, 35, 52 and 19% in predicting IDH mutation status, and 16, 15 and 14% in predicting 1p/19q codeletion status (p < 0.05). CONCLUSION: Radiomics analysis of quantitative maps from synthetic MRI provides a new quantitative imaging tool for the preoperative prediction of grades and molecular subtypes in diffuse gliomas.

Encoding independent wavefronts in a single metasurface for high-order optical vortex recognition.

The orbital angular momentum (OAM) of vortex beams has great potential in optical communications due to its communication confidentiality and low crosstalk. It is necessary to design a plausible OAM pattern recognition mechanism. Abandoning AI models that require large datasets, a single passive all-dielectric metasurface consisting of TiO2 nanopillars on a SiO2 substrate is used to recognize high-order optical vortexes. In this configuration, the proposed device is capable of simultaneously encoding the wavefront and the transmission paths in different incident OAM beams. Due to the presence of spin angular momentum (SAM), the vortex beam to be identified is spatially separated after passing through the metasurface. As a proof of concept, 14 signal channels are considered in the constructed metasurface, 12 of them can be encoded at will for the detection of any vortex beam with a predefined topological charge. These results make use of metasurfaces to enable OAM pattern recognition in an effective way, which may open avenues for the ultimate miniaturization of optical vortex communication and advanced OAM detection technologies.

Operating point control method for the Mach-Zehnder modulator in a phase-shift laser range finder.

An operating point control method is proposed for the Mach-Zehnder modulator (MZM) based on a dual-cascaded MZM structure. Unlike traditional methods with dither signals, the proposed method is advantageous because the components monitored in the control process are not masked by the spectrum noise floor and the drift direction is clearly determined at the quadrature point, thus imparting greater control stability. Additionally, the proposed control method is suitable for phase-shift laser range finders (PSLRFs). Compared with traditional methods, experimental results reveal that the proposed method increases the operating point stability of MZM from ±0.59° to ±0.36° within 2 h, resulting in better ranging stability than 17 µm in 1 min and 39 µm in 1 h in a PSLRF with a 200 MHz modulation frequency.

Bismuth-doped fiber amplifier based on a linear cavity double pass structure operating in the O + E band.

Finding suitable fiber amplifiers is one of the key strategies to increase the transmission capacity of fiber links. Recently, bismuth-doped fiber amplifiers (BDFAs) have attracted much attention due to their distinctive ultra-wideband luminescence properties. In this paper, we propose a linear cavity double pass structure for BDFA operating in the O and E bands. The design creates a linear cavity within the amplifier by combining a fiber Bragg grating (FBG) and a fiber mirror to achieve dual-wavelength pump at 1240 nm and 1310 nm. Meanwhile, the configuration of a circulator and mirror facilitates bidirectional signal propagation through the BDFA, resulting in a double-pass amplification structure. We have tested and analyzed the performance of the linear cavity double pass structure BDFA under different pump schemes and compared it with the conventional structure BDFA. The results show that the gain spectrum of the new structure is shifted toward longer wavelengths, and the gain band is extended from the O band to the O and E bands compared with the conventional structure. In particular, the linear cavity double pass structure BDFA has more relaxed requirements on the stability of the pump and signal power. This work provides a positive reference for the design, application, and development of BDFAs.

Nonlinear 3D Ligand-Based Metal-Organic Framework for Thermodynamic-Kinetic Synergistic Splitting of Mono-/Dibranched Hexane Isomers.

The selective splitting of hexane isomers without the use of energy-intensive phase-change processes is essential for the low-carbon production of clean fuels and also very challenging. Here, we demonstrate a strategy to achieve a complete splitting of the high-RON dibranched isomer from the monobranched and linear isomers, by using a nonlinear 3D ligand to form pillar-layered MOFs with delicate pore architecture and chemistry. Compared with its isoreticular MOFs with the same ted pillar but different linear 3D or linear 2D in-layer ligands, the new MOF constructed in this work, Cu(bhdc)(ted)0.5 (ZUL-C5), exhibited an interesting "channel switch" effect which creates pore space with reduced window size and channel dimensionality together with unevenly distributed alkyl-rich adsorption sites, contributing to a greatly enhanced ability to discriminate between mono- and dibranched isomers. Evidenced by a series of studies including adsorption equilibrium/kinetics/breakthrough tests, guest-loaded single-crystal/powder XRD measurement, and DFT-D modeling, a thermodynamic-kinetic synergistic mechanism in the separation was proposed, resulting in a record production time for high-purity 2,2-dimethylbutane along with a high yield.

Regulation of SETD2 maintains immune regulatory function in macrophages to suppress airway allergy.

SET domain-containing 2 (SETD2) is a histone methyltransferase. It regulates the activity of H3K36me3 to enhance gene transcription. Macrophages (Mϕs) are one of the cell types involved in immune response. The purpose of this study is to clarify the role of SETD2 in regulating the immune property of Mϕ. The Mφs were isolated from the bronchoalveolar lavage fluid (BALF) and analysed through flow cytometry and RNA sequencing. A mouse strain carrying Mφs deficient in SETD2 was used. A mouse model of airway allergy was established with the ovalbumin/alum protocol. Less expression of SETD2 was observed in airway Mϕs in patients with allergic asthma. SETD2 of M2 cells was associated with the asthmatic clinical response. Sensitization reduced the expression of SETD2 in mouse respiratory tract M2 cells, which is associated with the allergic reaction. Depletion of SETD2 in Mφs resulted in Th2 pattern inflammation in the lungs. SETD2 maintained the immune regulatory ability in airway M2 cells. SETD2 plays an important role in the maintenance of immune regulatory property of airway Mφs.

Sludge reduction and hydrogen production in a microbial photoelectrochemical cell with a g-C3N4/CQDs/BiOBr composite photocathode.

Hydrogen (H2) remains a pivotal clean energy source, and the emergence of Solar-powered Microbial Photoelectrochemical Cells (MPECs) presents promising avenues for H2 production while concurrently aiding organic matter degradation. This study introduces an MPEC system employing a g-C3N4/CQDs/BiOBr photocathode and a bioanode, successfully achieving simultaneous H2 production and sludge reduction. The research highlights the effective formation of a Z-type heterojunction in the g-C3N4/CQDs/BiOBr photocathode, substantially enhancing the photocurrent response under light conditions. Operating at - 0.4 V versus RHE, it demonstrated a current density of - 3.25 mA·cm-2, surpassing that of g-C3N4/BiOBr (-2.25 mA·cm-2) by 1.4 times and g-C3N4 (-2.04 mA·cm-2) by 1.6 times. When subjected to visible light irradiation and a 0.8 V applied bias voltage, the MPEC system achieved a current density of 1.0 mA·cm-2. The cumulative H2 production of the MPEC system reached 8.9 mL, averaging a production rate of 0.13 mL·h-1. In the anode chamber, the degradation rates of total chemical oxygen demand (TCOD), soluble chemical oxygen demand (SCOD), total suspended solids (TSS), volatile suspended solids (VSS), proteins, polysaccharides, and volatile fatty acids (VFA) in the sludge were recorded at 57.18%, 82.64%, 64.98%, 86.39%, 42.81%, 67.34%, and 29.01%, respectively.