Sample Size Determination and Study Design Impact on Dose-Scale Pharmacodynamic Bioequivalence: a Case Study Using Orlistat.

Dose-scale pharmacodynamic bioequivalence is recommended for evaluating the consistency of generic and innovator formulations of certain locally acting drugs, such as orlistat. This study aimed to investigate the standard methodology for sample size determination and the impact of study design on dose-scale pharmacodynamic bioequivalence using orlistat as the model drug. A population pharmacodynamic model of orlistat was developed using NONMEM 7.5.1 and utilized for subsequent simulations. Three different study designs were evaluated across various predefined relative bioavailability ratios of test/reference (T/R) formulations. These designs included Study Design 1 (2×1 crossover with T1 60 mg, R1 60 mg, and R2 120 mg), Study Design 2 (2×1 crossover with T2 120 mg, R1 60 mg, and R2 120 mg), and Study Design 3 (2×2 crossover with T1 60 mg, T2 120 mg, R1 60 mg, and R2 120 mg). Sample sizes were determined using a stochastic simulation and estimation approach. Under the same T/R ratio and power, Study Design 3 required the minimum sample size for bioequivalence, followed by Study Design 1, while Study Design 2 performed the worst. For Study Designs 1 and 3, a larger sample size was needed on the T/R ratio < 1.0 side for the same power compared to that on the T/R ratio > 1.0 side. The opposite asymmetry was observed for Study Design 2. We demonstrated that Study Design 3 is most effective for reducing the sample size for orlistat bioequivalence studies, and the impact of T/R ratio on sample size shows asymmetry.

A novel variant in GAS2 is associated with autosomal dominant nonsyndromic hearing impairment in a Chinese family.

Knockout of GAS2 (growth arrest-specific protein 2), causes disorganization and destabilization of microtubule bundles in supporting cells of the cochlear duct, leading to hearing loss in vivo. However, the molecular mechanism through which GAS2 variant results in hearing loss remains unknown. By Whole-exome sequencing, we identified a novel heterozygous splicing variant in GAS2 (c.616-2 A > G) as the only candidate mutation segregating with late-onset and progressive nonsyndromic hearing loss (NSHL) in a large dominant family. This splicing mutation causes an intron retention and produces a C-terminal truncated protein (named GAS2mu). Mechanistically, the degradation of GAS2mu via the ubiquitin-proteasome pathway is enhanced, and cells expressing GAS2mu exhibit disorganized microtubule bundles. Additionally, GAS2mu further promotes apoptosis by increasing the Bcl-xS/Bcl-xL ratio instead of through the p53-dependent pathway as wild-type GAS2 does, indicating that GAS2mu acts as a toxic molecule to exacerbate apoptosis. Our findings demonstrate that this novel variant of GAS2 promotes its own protein degradation, microtubule disorganization and cellular apoptosis, leading to hearing loss in carriers. This study expands the spectrum of GAS2 variants and elucidates the underlying pathogenic mechanisms, providing a foundation for future investigations of new therapeutic strategies to prevent GAS2-associated progressive hearing loss.

Single-cell enzymatic cascade synthesis of testolactone enabled by engineering of polycyclic ketone monooxygenase and multi-gene expression fine-tuning.

The synthesis of steroids is challenging through multistep steroidal core modifications with high site-selectivity and productivity. In this work, a novel enzymatic cascade system was constructed for synthesis of testolactone by specific C17 lactonization/Δ1-dehydrogenation from inexpensive androstenedione using an engineered polycyclic ketone monooxygenase (PockeMO) and an appropriate 3-ketosteroid-Δ1-dehydrogenase (ReKstD). The focused saturation mutagenesis in the substrate binding pocket was implemented for evolution of PockeMO to eliminate the bottleneck effect. A best mutant MU3 (I225L/L226V/L532Y) was obtained with 20-fold higher specific activity compared to PockeMO. The catalytic efficiency (kcat/Km) of MU3 was 171-fold higher and the substrate scope shifted to polycyclic ketones. Molecular dynamic simulations suggested that the activity was improved by stabilization of the pre-lactonization state and generation of productive orientation of 4-AD mediated by distal L532Y mutation. Based on that, the three genes, MU3, ReKstD and a ketoreductase for NADPH regeneration, were rationally integrated in one cell via expression fine-tuning to form the efficient single cell catalyst E. coli S9. The single whole-cell biocatalytic process was scaled up and could generate 9.0 g/L testolactone with the high space time yield of 1 g/L/h without steroidal by-product, indicating the potential for site-specific and one-pot synthesis of steroid.

Multienzymatic Cascade for Synthesis of Hydroxytyrosol via Two-Stage Biocatalysis.

Hydroxytyrosol, a naturally occurring compound with antioxidant and antiviral activity, is widely applied in the cosmetic, food, and nutraceutical industries. The development of a biocatalytic approach for producing hydroxytyrosol from simple and readily accessible substrates remains a challenge. Here, we designed and implemented an effective biocatalytic cascade to obtain hydroxytyrosol from 3,4-dihydroxybenzaldehyde and l-threonine via a four-step enzymatic cascade composed of seven enzymes. To prevent cross-reactions and protein expression burden caused by multiple enzymes expressed in a single cell, the designed enzymatic cascade was divided into two modules and catalyzed in a stepwise manner. The first module (FM) assisted the assembly of 3,4-dihydroxybenzaldehyde and l-threonine into (2S,3R)-2-amino-3-(3,4-dihydroxyphenyl)-3-hydroxypropanoic acid, and the second module (SM) entailed converting (2S,3R)-2-amino-3-(3,4-dihydroxyphenyl)-3-hydroxypropanoic acid into hydroxytyrosol. Each module was cloned into Escherichia coli BL21 (DE3) and engineered in parallel by fine-tuning enzyme expression, resulting in two engineered whole-cell catalyst modules, BL21(FM01) and BL21(SM13), capable of converting 30 mM 3,4-dihydroxybenzaldehyde to 28.7 mM hydroxytyrosol with a high space-time yield (0.88 g/L/h). To summarize, the current study proposes a simple and effective approach for biosynthesizing hydroxytyrosol from low-cost substrates and thus has great potential for industrial applications.

Efficacy and Safety of Ganyushu Granule in Treatment of Premenstrual Syndrome with Gan (Liver) Depression and Qi Stagnation Syndrome: A Randomized, Double-Blind, Multi-Center, Phase-II Clinical Trial.

OBJECTIVE: To confirm the efficacy and safety of Ganyushu Granule (GYSG) in treating premenstrual syndrome (PMS) in patients with Gan (Liver) depression and qi stagnation syndrome (GDQSS) and determine its effective dosage. METHODS: From June 2018 to March 2021, a total of 240 PMS women with GDQSS were included and randomly divided into 3 groups in a 1:1:1 ratio using central block randomization: high-dose GYSG group (n=78, GYSG 2 packs/time), low-dose GYSG group (n=82, GYSG and its simulant 1 pack/time), and placebo group (n=80, GYSG simulant 2 packs/time). Treatment with GYSG or placebo was given thrice daily and for up to 3 menstrual cycles. Primary outcomes were PMS diary (PMSD) score and premenstrual tension syndrome self-rating scale (PMTS). Secondary outcomes were Chinese medicine (CM) syndrome efficacy. PMSD, PMTS, and efficacy of CM were evaluated with menstrual cycles during the treatment period. Outcome indicators were analyzed after each menstrual cycle. All analyses were performed using an intention-to-treat method, and clinical safety was assessed. RESULTS: Of the 216 patients included in the effectiveness analysis, 70, 75, and 71 patients were in the high-, low-dose GYSG, and placebo groups, respectively. From the 2nd treatment cycle, the change in PMSD scores in the high- and low-dose groups was lower than that in the placebo group (P<0.05). PMTS scores in the high-dose GYSG group after the 1st treatment cycle was lower than that in the placebo group (P<0.05), while after the 3rd treatment cycle, that in the low-dose group was lower than that in the placebo group (P<0.05). After the 2nd treatment cycle, the high-dose GYSG group had the best CM syndrome efficacy (P<0.05). No serious adverse reactions were reported. CONCLUSIONS: GYSG was safe and well-tolerated at both doses for treating PMS patients with GDQSS. High-dose GYSG might be the optimal dose for a phase III trial. (Registration No. ChiCTR1800016595).

Effects of acute and chronic heat stress on the rumen microbiome in dairy goats.

Objective: The objective of this study was to reveal the influence of acute and chronic heat stress (HS) on the abundance and function of rumen microbiome and host metabolism. Methods: The forty mid-lactation goats were randomly divided into two artificial environments a control group and a heat-stressed group. This study was collected from two periods, 1 day and 28 days. The first day was defined as control 1 (CT1) and HS 1 (acute HS), and the last day was defined as CT28 and HS28 (chronic HS). On the first and last day, 6 dairy goats in each group were randomly selected to collect rumen liquid after the morning feeding through oral stomach tubes. The barn temperature and humidity were recorded every day. Results: Disruption of the rumen microbiome was observed under chronic HS, represented by an increase in the abundance of Prevotella and Bacteroidales (p<0.05), and upregulation of carbohydrate transport and metabolism functions (p<0.05). Additionally, the abundance of Succinimonas and Ruminobacter in chronic HS is lower than in acute HS (p<0.05), and the functions of intracellular trafficking, secretion and vesicular transport, and the cytoskeleton were downregulated (p<0.05). Conclusion: HS affected the interaction between the microbiota and host, thereby regulating milk production in dairy goats. These findings increased understanding of the crosstalk between hosts and microorganisms.

The safety of benzodiazepines and related drugs during pregnancy: an updated meta-analysis of cohort studies.

PURPOSE: The prevalence of benzodiazepines and related drugs (BZRDs) use during pregnancy increased sharply in recent years. Thus, there are concerns regarding the pregnancy outcomes following exposure to BZRDs. METHODS: Two electronic databases were thoroughly searched to identify related clinical studies published from inception until June 2023. English-language cohort studies with high-quality comparing antenatal BZRDs exposure to an unexposed group on any delivery outcome were included. RESULTS: Ten cohort studies that estimated adverse neonatal outcomes associated with exposure to BZRDs during pregnancy were included. Exposure to BZRDs during pregnancy was associated with an increased risk of congenital malformation [odds ratio (OR) 1.09, 95% confidence interval (CI) 1.05-1.13, p < 0.001], heart malformation (OR 1.13, 95% CI 1.04-1.22, p = 0.003), preterm birth (OR 1.45, 95% CI 1.23-1.7, p < 0.001), SGA (OR 1.18, 95% CI 1.08-1.29, P < 0.001), LBW (OR 1.42, 95% CI 1.25-1.6, p = 0.001) or low Apgar score (OR 1.42, 95% CI 1.08-1.87, p = 0.011),compared with no exposure. Further analyses limited to the first trimester exposure yielded consistent results. CONCLUSIONS: Exposure to BZRDs during pregnancy may be associated with several adverse neonatal outcomes. However, we could not rule out the potential indication confounding factor, further studies with high-quality that control for important confounders are still needed to verify our findings.

Characteristic cembrane-type diterpenoids with nitric oxide inhibitory activity from the gum resin of Boswellia carterii Birdw.

Five new characteristic cembrane-type diterpenoids (olibacartiols A-E, 1-5) were acquired from the gum resin of Boswellia carterii. The structures of these diterpenoids were characterized by detailed spectroscopic analysis, and compounds 1-3 were unambiguously confirmed by single-crystal X-ray diffraction experiments. The anti-inflammatory activities of the isolated compounds were evaluated using LPS-induced BV2 cell model and compounds 2-5 showed moderate NO inhibitory effects with IC50 values of 8.84 ± 1.02, 9.82 ± 1.95, 9.75 ± 2.24, and 7.39 ± 1.24 µM, respectively.

Associations between whole grains intake and new-onset hypertension: a prospective cohort study.

IMPORTANCE: Epidemiological evidences regarding the association between whole grain intake and the risk of new-onset hypertension are still controversial. OBJECTIVE: We aimed to investigate the relationship between whole grain intake and new-onset hypertension and examine possible effect modifiers in the general population. METHODS: A total of 10,973 participants without hypertension from the China Health and Nutrition Survey were enrolled, with follow-up beginning in 1997 and ending in 2015. Whole grain intake was assessed by 3 consecutive 24-h dietary recalls combined with a household food inventory. Multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression model after adjusting for potential risk factors. RESULTS: During a median follow-up of 7.0 years, 3,733 participants developed new-onset hypertension. The adjusted HRs (95% CIs) were as follows: for quartile 2 (HR: 0.52; 95% CI: 0.47-0.57), quartile 3 (HR: 0.46; 95% CI: 0.42-0.51), and quartile 4 (HR: 0.35; 95% CI: 0.31-0.38), compared with quartile 1. Different types of whole grain types, including wheat (adjusted HR, 0.35; 95% CI, 0.32-0.39), maize (adjusted HR, 0.50; 95% CI, 0.42-0.59), and millet (adjusted HR, 0.38; 95% CI, 0.30-0.48), showed significant associations with a reduced risk of hypertension. The association between whole grain intake and new-onset hypertension was stronger in individuals with older age (P for interaction < 0.001) and higher BMI (P for interaction < 0.001). CONCLUSION: Higher consumption of whole grains was significantly associated with a lower risk of new-onset hypertension. This study provides further evidence supporting the importance of increasing whole grain intake for hypertension prevention among Chinese adults.

MCTformer+: Multi-Class Token Transformer for Weakly Supervised Semantic Segmentation.

This paper proposes a novel transformer-based framework to generate accurate class-specific object localization maps for weakly supervised semantic segmentation (WSSS). Leveraging the insight that the attended regions of the one-class token in the standard vision transformer can generate class-agnostic localization maps, we investigate the transformer's capacity to capture class-specific attention for class-discriminative object localization by learning multiple class tokens. We present the Multi-Class Token transformer, which incorporates multiple class tokens to enable class-aware interactions with patch tokens. This is facilitated by a class-aware training strategy that establishes a one-to-one correspondence between output class tokens and ground-truth class labels. We also introduce a Contrastive-Class-Token (CCT) module to enhance the learning of discriminative class tokens, enabling the model to better capture the unique characteristics of each class. Consequently, the proposed framework effectively generates class-discriminative object localization maps from the class-to-patch attentions associated with different class tokens. To refine these localization maps, we propose the utilization of patch-level pairwise affinity derived from the patch-to-patch transformer attention. Furthermore, the proposed framework seamlessly complements the Class Activation Mapping (CAM) method, yielding significant improvements in WSSS performance on PASCAL VOC 2012 and MS COCO 2014. These results underline the importance of the class token for WSSS. The codes and models are publicly available here.

A comprehensive comparative genomic analysis revealed that plant growth promoting traits are ubiquitous in strains of Stenotrophomonas.

Stenotrophomonas strains, which are often described as plant growth promoting (PGP) bacteria, are ubiquitous in many environments. A total of 213 genomes of strains of Stenotrophomonas were analyzed using comparative genomics to better understand the ecological roles of these bacteria in the environment. The pan-genome of the 213 strains of Stenotrophomonas consists of 27,186 gene families, including 710 core gene families, 11,039 unique genes and 15,437 accessory genes. Nearly all strains of Stenotrophomonas harbor the genes for GH3-family cellulose degradation and GH2- and GH31-family hemicellulose hydrolase, as well as intact glycolysis and tricarboxylic acid cycle pathways. These abilities suggest that the strains of this genus can easily obtain carbon and energy from the environment. The Stenotrophomonas strains can respond to oxidative stress by synthesizing catalase, superoxide dismutase, methionine sulfoxide reductase, and disulfide isomerase, as well as managing their osmotic balance by accumulating potassium and synthesizing compatible solutes, such as betaine, trehalose, glutamate, and proline. Each Stenotrophomonas strain also contains many genes for resistance to antibiotics and heavy metals. These genes that mediate stress tolerance increase the ability of Stenotrophomonas strains to survive in extreme environments. In addition, many functional genes related to attachment and plant colonization, growth promotion and biocontrol were identified. In detail, the genes associated with flagellar assembly, motility, chemotaxis and biofilm formation enable the strains of Stenotrophomonas to effectively colonize host plants. The presence of genes for phosphate-solubilization and siderophore production and the polyamine, indole-3-acetic acid, and cytokinin biosynthetic pathways confer the ability to promote plant growth. These strains can produce antimicrobial compounds, chitinases, lipases and proteases. Each Stenotrophomonas genome contained 1-9 prophages and 17-60 genomic islands, and the genes related to antibiotic and heavy metal resistance and the biosynthesis of polyamines, indole-3-acetic acid, and cytokinin may be acquired by horizontal gene transfer. This study demonstrates that strains of Stenotrophomonas are highly adaptable for different environments and have strong potential for use as plant growth-promoting bacteria.

VCF2PCACluster: a simple, fast and memory-efficient tool for principal component analysis of tens of millions of SNPs.

Principal component analysis (PCA) is an important and widely used unsupervised learning method that determines population structure based on genetic variation. Genome sequencing of thousands of individuals usually generate tens of millions of SNPs, making it challenging for PCA analysis and interpretation. Here we present VCF2PCACluster, a simple, fast and memory-efficient tool for Kinship estimation, PCA and clustering analysis, and visualization based on VCF formatted SNPs. We implemented five Kinship estimation methods and three clustering methods for its users to choose from. Moreover, unlike other PCA tools, VCF2PCACluster possesses a clustering function based on PCA result, which enabling users to automatically and clearly know about population structure. We demonstrated the same accuracy but a higher performance of this tool in performing PCA analysis on tens of millions of SNPs compared to another popular PLINK2 software, especially in peak memory usage that is independent of the number of SNPs in VCF2PCACluster.

An improved technology for monitoring groundwater flow velocity and direction in fractured rock system based on colloidal particles motion.

The colloidal borescope, using colloidal particle motion, is used to monitor the flow velocities and directions of groundwater. It integrates advanced techniques such as microscopy, high-speed photography, and big data computing and enjoys high sensitivity at the micron level. However, In the same well, the groundwater flow velocity monitored by colloidal hole mirror is varies greatly from that obtained by conventional hydrogeological monitoring, such as pumping test. In order to solve this problem, the stability catcher and stratified packer are designed to control the interference of the vertical flow in drilling, and to monitor the flow velocity and direction of groundwater velocity at the target aquifer and target fracture. Five wells with different aquifers and different groundwater types were selected for monitoring in south-central China. The instantaneous velocity and direction are converted into east-west component and north-south component, the average velocity and direction is calculated according to the time of 10 min, and the particle trajectory diagram is established. Based on these results, it proposed a concept of cumulative flow velocity. Using curve-fitting equations, the limits of cumulative flow velocities as the monitoring time tends to infinity were then calculated as the actual flow velocities of the groundwater. The permeability coefficient of aquifer is calculated by using the fissure ratio of aquifer, hydraulic slope and flow velocity, and compared with the permeability coefficient obtained by pumping test. The results are as follows: (1) The variation coefficient of the instantaneous flow velocity measured at the same depth in the same well at different times is greater than that of the time average flow velocity and greater than that of the cumulative flow velocity. The variation coefficient of the actual velocity is the smallest, indicating that the risk of using the actual flow velocity is lower. (2) The variation coefficient of the flow rate monitored at different depths in the same well is mainly controlled by the properties of the aquifer. The more uniform water storage space in the aquifer, the smaller the variation coefficient. (3) The comparison between the permeability coefficient obtained by monitoring and the permeability coefficient obtained by pumping test shows that the flow of structural fissure water controlled by planar fissure is more surface flow, and the results are consistent. When the groundwater flow is controlled by pores and solution gaps, the flow channel is complicated, which is easy to produce turbulent flow, and the result consistency is poor. (4) According to different research accuracy requirements, different monitoring and calculation methods can be selected for different aquifers and groundwater types. Researches show that, the permeability coefficient calculated for the actual flow velocity in well DR01 is the same as that calculated for the pumping test. The aquifer characteristics reflected by the coefficient of variation of the actual flow velocity in the same aquifer are more realistic. The pumping test method obtains the comprehensive parameters of a certain aquifer, and this method can be used to monitor a certain fissure. In this paper, the new technology developed for monitoring, and the new algorithm established for data processing, can accurately obtain the flow velocity and direction of groundwater, using capsule hole mirror monitoring method. The key parameters of hydrogeology can be obtained by using one well, which can reduce the time and cost input and improve the work efficiency.

An artificial biocatalytic cascade for efficient synthesis of norepinephrine by combination of engineered L-threonine transaldolase with multi-enzyme expression fine-tuning.

Norepinephrine, a kind of ß-adrenergic receptor agonist, is commonly used for treating shocks and hypotension caused by a variety of symptoms. The development of a straightforward, efficient and environmentally friendly biocatalytic route for manufacturing norepinephrine remains a challenge. Here, we designed and realized an artificial biocatalytic cascade to access norepinephrine starting from 3, 4-dihydroxybenzaldehyde and L-threonine mediated by a tailored-made L-threonine transaldolase PsLTTA-Mu1 and a newly screened tyrosine decarboxylase ErTDC. To overcome the imbalance of multi-enzymes in a single cell, engineering of PsLTTA for improved activity and fine-tuning expression mode of multi-enzymes in single E.coli cells were combined, leading to a robust whole cell biocatalyst ES07 that could produce 100 mM norepinephrine with 99% conversion, delivering a highest time-space yield (3.38 g/L/h) ever reported. To summarized, the current study proposed an effective biocatalytic approach for the synthesis of norepinephrine from low-cost substrates, paving the way for industrial applications of enzymatic norepinephrine production.

PMAT: an efficient plant mitogenome assembly toolkit using low-coverage HiFi sequencing data.

Complete mitochondrial genomes (mitogenomes) of plants are valuable resources for nucleocytoplasmic interactions, plant evolution, and plant cytoplasmic male sterile line breeding. However, the complete assembly of plant mitogenomes is challenging due to frequent recombination events and horizontal gene transfers. Previous studies have adopted Illumina, PacBio, and Nanopore sequencing data to assemble plant mitogenomes, but the poor assembly completeness, low sequencing accuracy, and high cost limit the sampling capacity. Here, we present an efficient assembly toolkit (PMAT) for de novo assembly of plant mitogenomes using low-coverage HiFi sequencing data. PMAT has been applied to the de novo assembly of 13 broadly representative plant mitogenomes, outperforming existing organelle genome assemblers in terms of assembly accuracy and completeness. By evaluating the assembly of plant mitogenomes from different sequencing data, it was confirmed that PMAT only requires 1× HiFi sequencing data to obtain a complete plant mitogenome. The source code for PMAT is available at https://github.com/bichangwei/PMAT. The developed PMAT toolkit will indeed accelerate the understanding of evolutionary variation and breeding application of plant mitogenomes.

Tuning the electronic metal-carbon interactions in Lignin-based carbon-supported ruthenium-based electrocatalysts for enhanced hydrogen evolution reactions.

Ruthenium (Ru) nanoparticles dispersed on carbon support are promising electrocatalysts for hydrogen evolution reaction (HER) due to strong electronic metal-carbon interactions (EMCIs). Defects engineering in carbon supports is an effective strategy to adjust EMCIs. We prepared nitrogen/sulfur co-doped carbon supported Ru nanoparticles (Ru@N/S-LC) using sodium lignosulfonate and urea as feedstocks. Intrinsic S dopants from sodium lignosulfonate create rich S defects, thus enhancing the EMCIs within Ru@N/S-LC, leading a faster electron transfer between Ru nanoparticles and N/S-LC compared with N-doped carbon supported Ru nanoparticles (Ru@N-CC). The resulting Ru@N/S-LC exhibits an enhanced work function and a down-shifted d-band center, inducing stronger electron capturing ability and weaker hydrogen desorption energy than Ru@N-CC. Ru@N/S-LC requires only 7 and 94 mV overpotential in acidic medium and alkaline medium to achieve a current density of 10 mA cm-2. Density Functional Theory (DFT) calculations were utilized to clarify the impact of sulfur (S) doping and the mechanism underlying the notable catalytic activity of Ru@N/S-LC. This study offers a perspective for utilizing the natural dopants of biomass to adjust the EMCIs for electrocatalysts.

Smart responsive Fe/Mn nanovaccine triggers liver cancer immunotherapy via pyroptosis and pyroptosis-boosted cGAS-STING activation.

BACKGROUND: The prognosis for hepatocellular carcinoma (HCC) remains suboptimal, characterized by high recurrence and metastasis rates. Although metalloimmunotherapy has shown potential in combating tumor proliferation, recurrence and metastasis, current apoptosis-based metalloimmunotherapy fails to elicit sufficient immune response for HCC. RESULTS: A smart responsive bimetallic nanovaccine was constructed to induce immunogenic cell death (ICD) through pyroptosis and enhance the efficacy of the cGAS-STING pathway. The nanovaccine was composed of manganese-doped mesoporous silica as a carrier, loaded with sorafenib (SOR) and modified with MIL-100 (Fe), where Fe3+, SOR, and Mn2+ were synchronized and released into the tumor with the help of the tumor microenvironment (TME). Afterward, Fe3+ worked synergistically with SOR-induced immunogenic pyroptosis (via both the classical and nonclassical signaling pathways), causing the outflow of abundant immunogenic factors, which contributes to dendritic cell (DC) maturation, and the exposure of double-stranded DNA (dsDNA). Subsequently, the exposed dsDNA and Mn2+ jointly activated the cGAS-STING pathway and induced the release of type I interferons, which further led to DC maturation. Moreover, Mn2+-related T1 magnetic resonance imaging (MRI) was used to visually evaluate the smart response functionality of the nanovaccine. CONCLUSION: The utilization of metallic nanovaccines to induce pyroptosis-mediated immune activation provides a promising paradigm for HCC treatment.

Long-term air pollutants exposure and respiratory mortality: A large prospective cohort study.

Ambient air pollution is a major global health concern. Yet, no study has thoroughly assessed its link to respiratory mortality. Our research evaluated the combined and individual effects of air pollutants on respiratory mortality risks based on the UK Biobank. A total of 366,478 participants were studied. A Cox proportional hazards model was used to estimate the respiratory mortality risk from combined long-term exposure to five pollutants, summarized as a weighted air pollution score. During a median of 13.6 years of follow-up, 6113 deaths due to respiratory diseases were recorded. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) of respiratory diseases were 2.64 (2.05-3.39), 1.62 (1.23-2.12), 2.06 (1.73-2.45), 1.20 (1.16-1.25), and 1.07 (1.05-1.08) per 10 µg/m3 increase in PM2.5, PM2.5-10, PM10, NO2, and NOx, respectively. The air pollution score showed a dose-response association with an elevated respiratory mortality risk. The highest versus lowest quartile air pollution score was linked to a 44% increase in respiratory mortality risk (HR 1.44, 95% CI: 1.33-1.57), with consistent findings in subgroup and sensitivity analyses. Long-term individual and joint air-pollutant exposure showed a dose-response association with an increased respiratory mortality risk, highlighting the importance of a comprehensive air-pollutant assessment to protect public health.

Polycarboxyl ionic liquid functionalized Yb-MOFs nanoballs based dual-wavelength responsive photoelectrochemical aptasensor for the simultaneous determination of AFB1 and OTA.

Developing an accurate and precise approach for the simultaneous detection of ochratoxin A (OTA) and aflatoxin B1 (AFB1) is significant for food safety surveillance. Herein, a photoelectrochemical sensing platform was constructed based on polycarboxylic ionic liquid functionalized metal-organic framework integrated with gold nanoparticles (Yb-MOFs@AuNPs). Sulfhydryl functionalized hairpin DNA (hDNA) was immobilized on a Yb-MOFs@AuNPs modified glassy carbon electrode (GCE) surface through Au-S bond. After blocking residual active binding sites with BSA, gold nanoparticles-labeled AFB1 aptamer (AuNPs-Apt 1) and gold nanorods-labeled OTA aptamer (AuNRs-Apt 2) were introduced to construct a photoelectrochemical aptasensor for the simultaneous determination of AFB1 and OTA. Due to the surface plasmon resonance effect and the nanometer size effect of gold nanomaterials, the photoelectrochemical aptasensor can output photocurrent responses as being excited with different wavelengths at 520 nm and 808 nm, respectively. When the AFB1 and OTA concentration in the range of 0.001-50.0 ng mL-1, a good linear relationship between the photocurrent difference (ΔI) before and after recognizing targets and the logarithm of AFB1 or OTA concentration was obtained. The detection limits for AFB1 and OTA were 0.40 pg mL-1 and 0.19 pg mL-1, respectively. AFB1 and OTA in corn samples were detected simultaneously by the photoelectrochemical aptasensor.

Auxiliary Tasks Enhanced Dual-Affinity Learning for Weakly Supervised Semantic Segmentation.

Most existing weakly supervised semantic segmentation (WSSS) methods rely on class activation mapping (CAM) to extract coarse class-specific localization maps using image-level labels. Prior works have commonly used an off-line heuristic thresholding process that combines the CAM maps with off-the-shelf saliency maps produced by a general pretrained saliency model to produce more accurate pseudo-segmentation labels. We propose AuxSegNet + , a weakly supervised auxiliary learning framework to explore the rich information from these saliency maps and the significant intertask correlation between saliency detection and semantic segmentation. In the proposed AuxSegNet + , saliency detection and multilabel image classification are used as auxiliary tasks to improve the primary task of semantic segmentation with only image-level ground-truth labels. We also propose a cross-task affinity learning mechanism to learn pixel-level affinities from the saliency and segmentation feature maps. In particular, we propose a cross-task dual-affinity learning module to learn both pairwise and unary affinities, which are used to enhance the task-specific features and predictions by aggregating both query-dependent and query-independent global context for both saliency detection and semantic segmentation. The learned cross-task pairwise affinity can also be used to refine and propagate CAM maps to provide better pseudo labels for both tasks. Iterative improvement of segmentation performance is enabled by cross-task affinity learning and pseudo-label updating. Extensive experiments demonstrate the effectiveness of the proposed approach with new state-of-the-art WSSS results on the challenging PASCAL VOC and MS COCO benchmarks.