Development of a Competitive Chemiluminescent Assay for Quantitative Determination of TP53 Fusion Protein Using Reagent Strips.

Recent studies have shown that almost half of all cancers occur due to DNA damage. For the early diagnosis of cancer, a highly sensitized and swift identification for TP53 is needed since the corresponding TP53 protein is effectively recognized as "the guardian of the genome." To improve the detection sensitivity, numerous analytical methods were previously used for the determination of the TP53 protein, including denaturing high-performance liquid chromatography and enzyme-linked immunosorbent assay (ELISA). Currently, immunochromatographic tests (ICTs) that are simple to use, stable over time, and show low interference are regarded as valuable tools for the quick screening of food and environmental monitoring along with clinical diagnosis. ICTs often have limited sensitivity even if a variety of novel reporters possessing optimum photostability and improved brightness are used as signal-intensity reporters. Compared with N-(4-aminobutyl)-N-(ethylisoluminol) or luminol, a novel luminescent probe, 2',6'-diMethyl-4'-(N-succiniMidyloxycarbonyl) phenyl-10-sulfopropylacridiniuM-9-carboxylate (NSP-DMAE-NHS) has achieved a much higher efficiency, improvement in the biosensor's performance, and amplification of the signal without causing any damage to the biomolecule in terms of its biochemical activity. In this study, the reagent strip method was initially used to detect TP53 fusion protein by combining the advantages of NSP-DMAE-NHS and immunochromatography. In our experiment, the control and study lines on the strips were immobilized through HRP-conjugated goat anti-rabbit IgG and TP53 antigen, respectively. The optimized concentration of the anti-TP53 antibody-NSP-DMAE-NHS immunoconjugates was then added to the TP53 antigen samples. After, the test strips were inserted and left in the aforementioned buffer solution for an additional 20 min. Finally, a lab-made luminous measurement device was used to analyze the corresponding control and study lines on the strips. Under optimized conditions, this method was found to be ultrasensitive, with a wide range of linear responses from 0.0008 ng mL-1 to 1 µg mL-1 and a limit of detection of 0.0008 ng mL-1 (0.013 pM). Thus, a novel competitive chemiluminescent assay based on reagent strips was established for the determination of the TP53 fusion proteins. The strategy has potential applications for ultrasensitive detection in the early diagnosis of cancer.

Synthesis of S(IV)-Stereogenic Chiral Thio-Oxazolidinones via Palladium-Catalyzed Asymmetric [3+2] Annulations.

Organic molecules bearing chiral sulfur stereocenters exert a great impact on asymmetric catalysis and synthesis, chiral drugs, and chiral materials. Compared with acyclic ones, the catalytic asymmetric synthesis of thio-heterocycles has largely lagged behind due to the lack of efficient synthetic strategies. Here we establish the first modular platform to access chiral thio-oxazolidinones via Pd-catalyzed asymmetric [3+2] annulations of vinylethylene carbonates with sulfinylanilines. This protocol is featured by readily available starting materials, and high enantio- and diastereoselectivity. In particular, an unusual effect of a non-chiral supporting ligand on the diastereoselectivity was observed. Possible reaction mechanisms and stereocontrol models were proposed.

Single-Cell Transcriptome Sequence Profiling on the Morphogenesis of Secondary Hair Follicles in Ordos Fine-Wool Sheep.

The Ordos fine-wool sheep is a high-quality breed in China that produces superior natural textiles and raw materials such as wool and lamb meat. However, compared to the Australian Merino sheep, there is still a gap in terms of the wool fiber fineness and wool yield. The hair follicle is the main organ that controls the type of wool fiber, and the morphological changes in the secondary hair follicle are crucial in determining wool quality. However, the process and molecular mechanisms of hair follicle morphogenesis in Ordos fine-wool sheep are not yet clear. Therefore, analyzing the molecular mechanisms underlying the process of follicle formation is of great significance for improving the fiber diameter and wool production of Ordos fine-wool sheep. The differential expressed genes, APOD, POSTN, KRT5, and KRT15, which related to primary hair follicles and secondary hair follicles, were extracted from the dermal papillae. Based on pseudo-time analysis, the differentiation trajectories of dermal lineage cells and epidermal lineage cells in the Ordos fine-wool sheep were successfully constructed, providing a theoretical basis for breeding research in Ordos fine-wool sheep.

Preparation and p-phenylenediamine detection mechanism of a dialdehyde cellulose and a 7-amino-4-methylcoumarin-based fluorescent probe.

A novel fluorescent probe, fluorescent dialdehyde cellulose (FDAC), was prepared to detect p-phenylenediamine (PPD) in water samples conveniently and quickly. This was achieved by grafting 7-amino-4-methylcoumarin (AMC) onto dialdehyde cellulose (DAC) via an aldol-amine condensation reaction. This method is greener, more economical, and simpler than existing methods for preparing fluorescent probes. The probe was found to be more effective for PPD detection in polar solvents, with less interference from pH and other compounds present in the sample matrix. The photoluminescence of FDAC at λex/λem = 340/430 nm was statically quenched by PPD, allowing for accurate detection within the range of 10-100 µmol/L under optimal conditions, with a detection limit of 3.2 µmol/L (3 σ/s). Meanwhile, the Schiff base (-C=N- group) generated by the condensation of DAC and AMC increased the reaction activity of the fluorescent moiety and changed the AMC conjugated structure, making FDAC more susceptible to aminolysis with PPD than AMC. This study presents a promising solution for fluorescence detection of aniline compounds, with significant potential for application in fields such as environmental analysis.

Engineered Probiotic-Based Personalized Cancer Vaccine Potentiates Antitumor Immunity through Initiating Trained Immunity.

Cancer vaccines hold great potential for clinical cancer treatment by eliciting T cell-mediated immunity. However, the limited numbers of antigen-presenting cells (APCs) at the injection sites, the insufficient tumor antigen phagocytosis by APCs, and the presence of a strong tumor immunosuppressive microenvironment severely compromise the efficacy of cancer vaccines. Trained innate immunity may promote tumor antigen-specific adaptive immunity. Here, a personalized cancer vaccine is developed by engineering the inactivated probiotic Escherichia coli Nissle 1917 to load tumor antigens and ß-glucan, a trained immunity inducer. After subcutaneous injection, the cancer vaccine delivering model antigen OVA (BG/OVA@EcN) is highly accumulated and phagocytosed by macrophages at the injection sites to induce trained immunity. The trained macrophages may recruit dendritic cells (DCs) to facilitate BG/OVA@EcN phagocytosis and the subsequent DC maturation and T cell activation. In addition, BG/OVA@EcN remarkably enhances the circulating trained monocytes/macrophages, promoting differentiation into M1-like macrophages in tumor tissues. BG/OVA@EcN generates strong prophylactic and therapeutic efficacy to inhibit tumor growth by inducing potent adaptive antitumor immunity and long-term immune memory. Importantly, the cancer vaccine delivering autologous tumor antigens efficiently prevents postoperative tumor recurrence. This platform offers a facile translatable strategy to efficiently integrate trained immunity and adaptive immunity for personalized cancer immunotherapy.

Expected and Unexpected Products from the Biochemical Oxidation of Bacterial Alkylquinolones with CYP4F11.

2-Alkylquinolones are a class of microbial natural products primarily produced in the Pseudomonas and Burkholderia genera that play a key role in modulating quorum sensing. Bacterial alkylquinolones were synthesized and then subjected to oxidative biotransformation using human cytochrome P450 enzyme CYP4F11, heterologously expressed in the fission yeast Schizosaccharomyces pombe. This yielded a range of hydroxylated and carboxylic acid derivatives which had undergone ω-oxidation of the 2-alkyl chain, the structures of which were determined by analysis of NMR and MS data. Oxidation efficiency depended on chain length, with a chain length of eight or nine carbon atoms proving optimal for high yields. Homology modeling suggested that Glu233 was relevant for binding, due to the formation of a hydrogen bond from the quinolone nitrogen to Glu233, and in this position only the longer alkyl chains could come close enough to the heme moiety for effective oxidation. In addition to the direct oxidation products, a number of esters were also isolated, which was attributed to the action of endogenous yeast enzymes on the newly formed ω-hydroxy-alkylquinolones. ω-Oxidation of the alkyl chain significantly reduced the antimicrobial and antibiofilm activity of the quinolones.

Genomic Selection for Live Weight in the 14th Month in Alpine Merino Sheep Combining GWAS Information.

Alpine Merino Sheep is a novel breed reared from Australian Merino Sheep as the father and Gansu Alpine Fine-Wool Sheep as the mother, living all year in cold and arid alpine areas with exceptional wool quality and meat performance. Body weight is an important economic trait of the Alpine Merino Sheep, but there is limited research on identifying the genes associated with live weight in the 14th month for improving the accuracy of the genomic prediction of this trait. Therefore, this study's sample comprised 1310 Alpine Merino Sheep ewes, and the Fine Wool Sheep 50K Panel was used for genome-wide association study (GWAS) analysis to identify candidate genes. Moreover, the trial population (1310 ewes) in this study was randomly divided into two groups. One group was used as the population for GWAS analysis and screened for the most significant top 5%, top 10%, top 15%, and top 20% SNPs to obtain prior marker information. The other group was used to estimate the genetic parameters based on the weight assigned by heritability combined with different prior marker information. The aim of this study was to compare the accuracy of genomic breeding value estimation when combined with prior marker information from GWAS analysis with the optimal linear unbiased prediction method for genome selection (GBLUP) for the breeding value of target traits. Finally, the accuracy was evaluated using the five-fold cross-validation method. This research provides theoretical and technical support to improve the accuracy of sheep genome selection and better guide breeding. The results demonstrated that eight candidate genes were associated with GWAS analysis, and the gene function query and literature search results suggested that FAM184B, NCAPG, MACF1, ANKRD44, DCAF16, FUK, LCORL, and SYN3 were candidate genes affecting live weight in the 14th month (WT), which regulated the growth of muscle and bone in sheep. In genome selection analysis, the heritability of GBLUP to calculate the WT was 0.335-0.374, the accuracy after five-fold cross-verification was 0.154-0.190, and after assigning different weights to the top 5%, top 10%, top 15%, and top 20% of the GWAS results in accordance with previous information to construct the G matrix, the accuracy of the WT in the GBLUP model was improved by 2.59-7.79%.

Tumor-repopulating cell-derived microparticles elicit cascade amplification of chemotherapy-induced antitumor immunity to boost anti-PD-1 therapy.

Immune checkpoint blockade (ICB) therapy, particularly antibodies targeting the programmed death receptor 1 (PD-1) and its ligand (PD-L1), has revolutionized cancer treatment. However, its efficacy as a standalone therapy remains limited. Although ICB therapy in combination with chemotherapy shows promising therapeutic responses, the challenge lies in amplifying chemotherapy-induced antitumor immunity effectively. This relies on efficient drug delivery to tumor cells and robust antigen presentation by dendritic cells (DCs). Here, we developed tumor-repopulating cell (TRC)-derived microparticles with exceptional tumor targeting to deliver doxorubicin (DOX@3D-MPs) for improve anti-PD-1 therapy. DOX@3D-MPs effectively elicit immunogenic tumor cell death to release sufficient tumor antigens. Heat shock protein 70 (HSP70) overexpressed in DOX@3D-MPs contributes to capturing tumor antigens, promoting their phagocytosis by DCs, and facilitating DCs maturation, leading to the activation of CD8+ T cells. DOX@3D-MPs significantly enhance the curative response of anti-PD-1 treatment in large subcutaneous H22 hepatoma, orthotopic 4T1 breast tumor and Panc02 pancreatic tumor models. These results demonstrate that DOX@3D-MPs hold promise as agents to improve the response rate to ICB therapy and generate long-lasting immune memory to prevent tumor relapse.

Global DNA Methylation, miRNA, and mRNA Profiles in Sheep Skeletal Muscle Promoted by Hybridization.

With the development of high-throughput sequencing technology, several nongenetic variations, including noncoding RNAs such as miRNAs, and DNA methylation, have been found to play an important role in animal muscle development and fat metabolism. In this study, Southdown and Suffolk were selected as male parents for hybridization with Hu sheep (Southdown × Hu (NH), Suffolk × Hu (SH), and Hu × Hu (HH)). RNA sequencing, bisulfite sequencing, and small-RNA sequencing were used to study the methylation patterns and differences in miRNA and mRNA expression in the F1 sheep longissimus dorsi muscle tissue. We identified 765 differentially expressed genes (DEGs), 10,161 differentially methylated regions (DMRs), and 164 differentially expressed miRNAs, which were significantly enriched in AMPK signaling, fatty acid degradation, metabolism, and other related pathways (P < 0.05). In addition, we constructed a DNA methylation-mRNA and miRNA-mRNA coexpression network. A total of 42 common genes were identified from DMRs and DEGs. Importantly, we predicted that 33 differentially expressed miRNAs directly or indirectly targeted the SLC27A6. The data obtained in this study provide useful information and evidence to support further understanding of the miRNA and DNA methylation of key genes regulating muscle growth and fat metabolism in hybrid sheep populations.

Transcriptomics and metabolomics reveal improved performance of Hu sheep on hybridization with Southdown sheep.

Consumers are increasingly demanding high-quality mutton. Cross breeding can improve meat quality and is widely used in sheep breeding. However, little is known about the molecular mechanism of cross breeding sheep meat quality. In this study, male Southdown and female Hu sheep were hybridized. The slaughter performance and longissimus dorsi quality of the 6-month-old hybrid offspring were measured, and the longissimus dorsi of the hybrid offspring was analyzed by transcriptomics and metabolomics to explore the effect of cross breeding on meat quality. The results showed that the production performance of Southdown × Hu F1 sheep was significantly improved, the carcass fat content was significantly decreased, and the eating quality of Southdown × Hu F1 sheep were better. Compared with the HS group (Hu × Hu), the NH group (Southdown × Hu) had 538 differentially expressed genes and 166 differentially expressed metabolites (P < 0.05), which were significantly enriched in amino acid metabolism and other related pathways. Up-regulated genes METTL21C, PPARGC1A and down-regulated gene WFIKKN2 are related to muscle growth and development. Among them, the METTL21C gene, which is related to muscle development, was highly correlated with carnosine, a metabolite related to meat quality (correlation > 0.6 and P < 0.05). Our results provide further understanding of the molecular mechanism of cross breeding for sheep muscle growth and meat quality optimization.

Cell microparticles loaded with tumor antigen and resiquimod reprogram tumor-associated macrophages and promote stem-like CD8+ T cells to boost anti-PD-1 therapy.

The durable response rate to immune checkpoint blockade such as anti-programmed cell death-1 (PD-1) antibody remains relatively low in hepatocellular carcinoma (HCC), mainly depending on an immunosuppressive microenvironment with limited number of CD8+ T cells, especially stem-like CD8+ T cells, in tumor tissues. Here we develop engineered microparticles (MPs) derived from alpha-fetoprotein (AFP)-overexpressing macrophages to load resiquimod (R848@M2pep-MPsAFP) for enhanced anti-PD-1 therapy in HCC. R848@M2pep-MPsAFP target and reprogram immunosuppressive M2-like tumor-associated macrophages (TAMs) into M1-like phenotype. Meanwhile, R848@M2pep-MPsAFP-reprogrammed TAMs act as antigen-presenting cells, not only presenting AFP antigen to activate CD8+ T cell-mediated antitumor immunity, but also providing an intra-tumoral niche to maintain and differentiate stem-like CD8+ T cells. Combination immunotherapy with anti-PD-1 antibody generates strong antitumor immune memory and induces abundant stem-like CD8+ T cell proliferation and differentiation to terminally exhausted CD8+ T cells for long-term immune surveillance in orthotopic and autochthonous HCC preclinical models in male mice. We also show that the R848-loaded engineered MPs derived from macrophages overexpressing a model antigen ovalbumin (OVA) can improve anti-PD-1 therapy in melanoma B16-OVA tumor-bearing mice. Our work presents a facile and generic strategy for personalized cancer immunotherapy to boost anti-PD-1 therapy.

Hydrophobicity-Adaptive Polymers Trigger Fission of Tumor-Cell-Derived Microparticles for Enhanced Anticancer Drug Delivery.

Tumor-cell-derived microparticles (MPs) can function as anticancer drug-delivery carriers. However, short blood circulation time, large-size-induced insufficient tumor accumulation and penetration into tumor parenchyma, as well as limited cellular internalization by tumor cells and cancer stem cells (CSCs), and difficult intracellular drug release restrict the anticancer activity of tumor-cell-derived MP-based drug-delivery systems. In this work, hydrophobicity-adaptive polymers based on poly(N-isopropylacrylamide) are anchored to tumor-cell-derived MPs for enhanced delivery of the anticancer drug doxorubicin (DOX). The polymers are hydrophilic in blood to prolong the circulation time of DOX-loaded MPs (DOX@MPs), while rapidly switching to hydrophobic at the tumor acidic microenvironment. The hydrophobicity of polymers drives the fission of tumor-cell-derived MPs to form small vesicles, facilitating tumor accumulation, deep tumor penetration, and efficient internalization of DOX@MPs into tumor cells and CSCs. Subsequently, the hydrophobicity of polymers in acidic lysosomes further promotes DOX release to nuclei for strong cytotoxicity against tumor cells and CSCs. The work provides a facile and simple strategy for improved anticancer drug delivery of tumor-cell-derived MPs.

Security- and Reliability-Guaranteed Transmission Control of Time-Sensitive Physical Layer Security Systems.

In this paper, we consider information transmission over a three-node physical layer security system. Based on the imperfect estimations of the main channel and the eavesdropping channel, we propose reducing the outage probability and interception probability by hindering transmissions in cases where the main channel is too strong or too weak, which is referred to as an SNR-gated transmission control scheme. Specifically, Alice gives up its chance to transmit a packet if the estimated power gain of the main channel is smaller than a certain threshold so that possible outages can be avoided; Alice also becomes silent if the estimated power gain is larger than another threshold so that possible interceptions at Eve can be avoided. We also consider the timeliness of the network in terms of the violation probability of the peak age of information (PAoI). We present the outage probability, interception probability, and PAoI violation probability explicitly; we also investigate the trade-off among these probabilities, considering their weight sum. Our numerical and Monte Carlo results show that by using the SNR-gated transmission control, both the outage probability and the interception probability are reduced.

Functionalized Hydrogel-Based Wearable Gas and Humidity Sensors.

Breathing is an inherent human activity; however, the composition of the air we inhale and gas exhale remains unknown to us. To address this, wearable vapor sensors can help people monitor air composition in real time to avoid underlying risks, and for the early detection and treatment of diseases for home healthcare. Hydrogels with three-dimensional polymer networks and large amounts of water molecules are naturally flexible and stretchable. Functionalized hydrogels are intrinsically conductive, self-healing, self-adhesive, biocompatible, and room-temperature sensitive. Compared with traditional rigid vapor sensors, hydrogel-based gas and humidity sensors can directly fit human skin or clothing, and are more suitable for real-time monitoring of personal health and safety. In this review, current studies on hydrogel-based vapor sensors are investigated. The required properties and optimization methods of wearable hydrogel-based sensors are introduced. Subsequently, existing reports on the response mechanisms of hydrogel-based gas and humidity sensors are summarized. Related works on hydrogel-based vapor sensors for their application in personal health and safety monitoring are presented. Moreover, the potential of hydrogels in the field of vapor sensing is elucidated. Finally, the current research status, challenges, and future trends of hydrogel gas/humidity sensing are discussed.

Engineering Smart Composite Hydrogels for Wearable Disease Monitoring.

Growing health awareness triggers the public's concern about health problems. People want a timely and comprehensive picture of their condition without frequent trips to the hospital for costly and cumbersome general check-ups. The wearable technique provides a continuous measurement method for health monitoring by tracking a person's physiological data and analyzing it locally or remotely. During the health monitoring process, different kinds of sensors convert physiological signals into electrical or optical signals that can be recorded and transmitted, consequently playing a crucial role in wearable techniques. Wearable application scenarios usually require sensors to possess excellent flexibility and stretchability. Thus, designing flexible and stretchable sensors with reliable performance is the key to wearable technology. Smart composite hydrogels, which have tunable electrical properties, mechanical properties, biocompatibility, and multi-stimulus sensitivity, are one of the best sensitive materials for wearable health monitoring. This review summarizes the common synthetic and performance optimization strategies of smart composite hydrogels and focuses on the current application of smart composite hydrogels in the field of wearable health monitoring.

Prediction of nano, fine, and medium colloidal phosphorus in agricultural soils with machine learning.

Soil colloids have been shown to play a critical role in soil phosphorus (P) mobility and transport. However, identifying the potential mechanisms behind colloidal P (Pcoll) release and the key influencing factors remains a blind spot. Herein, a machine learning approach (random forest (RF) coupled with partial dependence plot analyses) was applied to determine the effects of different soil physicochemical parameters on Pcoll content in three colloidal subfractions (i.e., nano- (NC): 1-20 nm, fine- (FC): 20-220 nm and medium-sized colloids (MC): 220-450 nm) based on a regional dataset of 12 farmlands in Zhejiang Province, China. RF successfully predicted Pcoll content (R2 = 0.98). Results showed that colloidal- organic carbon (OCcoll) and minerals were the major determinants of total Pcoll content (1-450 nm); their critical values for increasing Pcoll release were 87.0 mg L-1 for OCcoll, 11.0 mg L-1 for iron (Fecoll) or aluminium (Alcoll), 2.6 mg L-1 for calcium (Cacoll), 9.0 mg L-1 for magnesium (Mgcoll), 2.5 mg L-1 for silicon (Sicoll), and 1.4 mg L-1 for manganese (Mncoll). Among three colloidal subfractions, the major factors determining Pcoll were soil Olsen-P (POlsen; 125.0 mg kg-1), Cacoll (2.5 mg L-1), and colloidal P saturation (21.0%) in NC; Mncoll (1.5 mg L-1), Mgcoll (6.8 mg L-1), and POlsen (135.0 mg kg-1) in FC; while Mncoll (1.5 mg L-1), Alcoll (2.5 mg L-1), and Fecoll (3.8 mg L-1) in MC, respectively. OCcoll had a considerable effect in the three fractions, with critical values of 80.0 mg L-1 in NC or FC, and 50.0 mg L-1 in MC. Our study concluded that the information gleaned using the RF model can be used as crucial evidence to identify the key determinants of different size fractionated Pcoll contents. However, we still need to discover one or more easy-to-measure parameters that can help us better predict Pcoll.

Nano and fine colloids suspended in the soil solution regulate phosphorus desorption and lability in organic fertiliser-amended soils.

Mobile colloids impact phosphorus (P) binding and transport in agroecosystems. However, their relationship to P-lability and their relative importance to P-bioavailability is unclear. In soils amended with organic fertilisers, we investigated the effects of nano (NC; 1-20 nm), fine (FC; 20-220 nm), and medium (MC; 220-450 nm) colloids suspended in soil solution on soil P-desorption and lability. The underlying hypothesis is that mobile colloids of different sizes, i.e., NC, FC, and MC, may contribute differently to P-lability in soils enriched with organic fertiliser. NC- and FC-bound Pcoll were positively correlated with P-lability parameters from diffusive gradient in thin films (DGTA-labile P concentration, r ≥ 0.88; and DGTA-effective P concentration, r ≥ 0.87). The corresponding relations with MC-bound Pcoll are weaker (r values of 0.50 and 0.51). NC- and FC-bound Pcoll were also strongly correlated with soil P-resupply (r ≥ 0.64) and desorption (r ≥ 0.79) parameters during DGTA deployment, and the mobility of these colloids was corroborated by electron microscopy of DGTA gels. MC-bound Pcoll was negatively correlated with the solid-to-solution distribution coefficient (r = -0.42), indicating this fraction is unlikely to be the source of P-release from the solid phase after P-depletion from the soil solution. We conclude that NC and FC mainly contribute to regulating soil desorbable-P supply to the soil solution in the DGTA depletion zone (in vitro proxy for plant rhizosphere), and consequently may act as critical conditioners of P-bioavailability, whereas MC tends to form complexes that lead to P-occlusion rather than lability.

Developing the novel diagnostic model and potential drugs by integrating bioinformatics and machine learning for aldosterone-producing adenomas.

Background: Aldosterone-producing adenomas (APA) are a common cause of primary aldosteronism (PA), a clinical syndrome characterized by hypertension and electrolyte disturbances. If untreated, it may lead to serious cardiovascular complications. Therefore, there is an urgent need for potential biomarkers and targeted drugs for the diagnosis and treatment of aldosteronism. Methods: We downloaded two datasets (GSE156931 and GSE60042) from the GEO database and merged them by de-batch effect, then screened the top50 of differential genes using PPI and enriched them, followed by screening the Aldosterone adenoma-related genes (ARGs) in the top50 using three machine learning algorithms. We performed GSEA analysis on the ARGs separately and constructed artificial neural networks based on the ARGs. Finally, the Enrich platform was utilized to identify drugs with potential therapeutic effects on APA by tARGseting the ARGs. Results: We identified 190 differential genes by differential analysis, and then identified the top50 genes by PPI, and the enrichment analysis showed that they were mainly enriched in amino acid metabolic pathways. Then three machine learning algorithms identified five ARGs, namely, SST, RAB3C, PPY, CYP3A4, CDH10, and the ANN constructed on the basis of these five ARGs had better diagnostic effect on APA, in which the AUC of the training set is 1 and the AUC of the validation set is 0.755. And then the Enrich platform identified drugs tARGseting the ARGs with potential therapeutic effects on APA. Conclusion: We identified five ARGs for APA through bioinformatic analysis and constructed Artificial neural network (ANN) based on them with better diagnostic effects, and identified drugs with potential therapeutic effects on APA by tARGseting these ARGs. Our study provides more options for the diagnosis and treatment of APA.

A two-sample mendelian randomization analysis excludes causal relationships between non-alcoholic fatty liver disease and kidney stones.

Objectives: Non-alcoholic fatty liver disease (NAFLD) has been linked to an increased risk of kidney stones in prior observational studies, However, the results are inconsistent, and the causality remains to be established. We aimed to investigate the potential causal relationship between NAFLD and kidney stones using two-sample Mendelian randomization (MR). Methods: Genetic instruments were used as proxies for NAFLD. Summary-level data for the associations of exposure-associated SNPs with kidney stones were obtained from the UK Biobank study (6536 cases and 388,508 controls) and the FinnGen consortium (9713 cases and 366,693 non-cases). MR methods were conducted, including inverse variance weighted method (IVW), MR-Egger, weighted median, and MR-PRESSO. MR-Egger Regression Intercept and Cochran's Q test were used to assess the directional pleiotropy and heterogeneity. Results: cALT-associated NAFLD did not exhibit an association with kidney stones in the Inverse variance weighted (IVW) methods, in both the FinnGen consortium (OR: 1.02, 95%CI: 0.94-1.11, p = 0.632) and the UKBB study (OR: 1.000, 95%CI: 0.998-1.002, p = 0.852). The results were consistent in European ancestry (FinnGen OR: 1.05, 95%CI: 0.98-1.14, p = 0.144, UKBB OR: 1.000, 95%CI: 0.998-1.002, p = 0.859). IVW MR analysis also did not reveal a significant causal relationship between NAFLD and the risk of kidney stone for the other three NAFLD-related traits, including imaging-based, biopsy-confirmed NAFLD, and more stringent biopsy-confirmed NAFLD. The results remained consistent and robust in the sensitivity analysis. Conclusions: The MR study did not provide sufficient evidence to support the causal associations of NAFLD with kidney stones.

Humidity Sensing of Stretchable and Transparent Hydrogel Films for Wireless Respiration Monitoring.

Respiratory monitoring plays a pivotal role in health assessment and provides an important application prospect for flexible humidity sensors. However, traditional humidity sensors suffer from a trade-off between deformability, sensitivity, and transparency, and thus the development of high-performance, stretchable, and low-cost humidity sensors is urgently needed as wearable electronics. Here, ultrasensitive, highly deformable, and transparent humidity sensors are fabricated based on cost-effective polyacrylamide-based double network hydrogels. Concomitantly, a general method for preparing hydrogel films with controllable thickness is proposed to boost the sensitivity of hydrogel-based sensors due to the extensively increased specific surface area, which can be applied to different polymer networks and facilitate the development of flexible integrated electronics. In addition, sustainable tapioca rich in hydrophilic polar groups is introduced for the first time as a second cross-linked network, exhibiting excellent water adsorption capacity. Through the synergistic optimization of structure and composition, the obtained hydrogel film exhibits an ultrahigh sensitivity of 13,462.1%/%RH, which is unprecedented. Moreover, the hydrogel film-based sensor exhibits excellent repeatability and the ability to work normally under stretching with even enhanced sensitivity. As a proof of concept, we integrate the stretchable sensor with a specially designed wireless circuit and mask to fabricate a wireless respiratory interruption detection system with Bluetooth transmission, enabling real-time monitoring of human health status. This work provides a general strategy to construct high-performance, stretchable, and miniaturized hydrogel-based sensors as next-generation wearable devices for real-time monitoring of various physiological signals.