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Abstract Background Bacterial small regulatory RNA (sRNA) plays a crucial role in cell metabolism and could be used as a new potential drug target in the treatment of pathogen-induced disease. However, experimental methods for identifying sRNAs still require a large investment of human and material resources. Methods In this study, we propose a novel sRNA prediction model called sRNAdeep based on the DistilBERT feature extraction and TextCNN methods. The sRNA and non-sRNA sequences of bacteria were considered as sentences and then fed into a composite model consisting of deep learning models to evaluate classification performance. Results By filtering sRNAs from BSRD database, we obtained a validation dataset comprised of 2438 positive and 4730 negative samples. The benchmark experiments showed that sRNAdeep displayed better performance in the various indexes compared to previous sRNA prediction tools. By applying our tool to Mycobacterium tuberculosis (MTB) genome, we have identified 21 sRNAs within the intergenic and intron regions. A set of 272 targeted genes regulated by these sRNAs were also captured in MTB. The coding proteins of two genes (lysX and icd1) are implicated in drug response, with significant active sites related to drug resistance mechanisms of MTB. Conclusion In conclusion, our newly developed sRNAdeep can help researchers identify bacterial sRNAs more precisely and can be freely available from https://github.com/pyajagod/sRNAdeep.git .

Abstract Background LDL receptor‐related protein‐1 (LRP1) is a cell‐surface receptor that functions in diverse physiological pathways. We previously demonstrated that hepatocyte‐specific LRP1 deficiency (hLRP1KO) promotes diet‐induced insulin resistance and increases hepatic gluconeogenesis in mice. However, it remains unclear whether LRP1 regulates hepatic glycogenesis. Methods Insulin signaling, glycogenic gene expression, and glycogen content were assessed in mice and HepG2 cells. The pcDNA 3.1 plasmid and adeno‐associated virus serotype 8 vector (AAV8) were used to overexpress the truncated β‐chain (β∆) of LRP1 both in vitro and in vivo. Results On a normal chow diet, hLRP1KO mice exhibited impaired insulin signaling and decreased glycogen content. Moreover, LRP1 expression in HepG2 cells was significantly repressed by palmitate in a dose‐ and time‐dependent manner. Both LRP1 knockdown and palmitate treatment led to reduced phosphorylation of Akt and GSK3β, increased levels of phosphorylated glycogen synthase (GYS), and diminished glycogen synthesis in insulin‐stimulated HepG2 cells, which was restored by exogenous expression of the β∆‐chain. By contrast, AAV8‐mediated hepatic β∆‐chain overexpression significantly improved the insulin signaling pathway, thus activating glycogenesis and enhancing glycogen storage in the livers of high‐fat diet (HFD)‐fed mice. Conclusion Our data revealed that LRP1, especially its β‐chain, facilitates hepatic glycogenesis by improving the insulin signaling pathway, suggesting a new therapeutic strategy for hepatic insulin resistance‐related diseases.

Abstract In the mechanical cutting industry, trial production is used for predicting and evaluating the quality of product processes before batch production, and it can be expressed through the qualification rate. However, it cannot objectively and comprehensively evaluate the quality of product processes. This study optimizes the analysis of outliers and stability in mathematical statistics to better apply it in the mechanical cutting industry; then, it combines them with process capability analysis. Simultaneously, considering the non-normal distribution of process parameters, a batch production-prediction model is proposed. The reliability of batch production-prediction model is verified by the diameter, roundness and roughness of structural common samples. Meanwhile, for other mechanical parts in the mechanical cutting industry, the model proposed in this paper can be used to quickly and accurately predict and evaluate batch production.

Abstract The effects of wind erosion, one of the crucial causes of soil desertification in the world, on the terrestrial ecosystem are well known. However, ecosystem responses regarding soil microbial carbon metabolism to sand deposition caused by wind erosion, a crucial driver of biogeochemical cycles, remain largely unclear. In this study, we collected soil samples from typical aeolian deposition farmland in the Songnen Plain of China to evaluate the effects of sand deposition on soil properties, microbial communities, and carbon metabolism function. We also determined the reads number of carbon metabolism-related genes by high-throughput sequencing technologies and evaluated the association between sand deposition and them. The results showed that long-term sand deposition resulted in soil infertile, roughness, and dryness. The impacts of sand deposition on topsoil were more severe than on deep soil. The diversity of soil microbial communities was significantly reduced due to sand deposition. The relative abundances of Nitrobacteraceae, Burkholderiaceae, and Rhodanobacteraceae belonging to α-Proteobacteria significantly decreased, while the relative abundances of Streptomycetaceae and Geodermatophilaceae belonging to Actinobacteria increased. The results of the metagenomic analysis showed that the gene abundances of carbohydrate metabolism and carbohydrate-activity enzyme (GH and CBM) significantly decreased with the increase of sand deposition amount. The changes in soil microbial community structure and carbon metabolism decreased soil carbon emissions and carbon cycling in aeolian deposition farmland, which may be the essential reasons for land degradation in aeolian deposition farmland.

BackgroundOrnithine transcarbamylase deficiency (OTCD), a rare hereditary disease caused by gene mutation of ornithine transcarbamylase (OTC), is the most prevalent type among urea cycle disorders. OTCD typically leads to mitochondrial enzyme dysfunction, preventing the synthesis of citrulline from carbamoyl phosphate and ornithine, and is characterized by a remarkable increase in blood ammonia. Specific symptoms may include neurological abnormalities, growth retardation, and other manifestations.MethodsWe presented a case of a child diagnosed with OTCD (OMIM: 311250). By using whole-genome sequencing (WGS) for the pedigree and in-depth whole-exome sequencing (WES), we aimed to identify the disease-causing genes. Gene mutation prediction tools were employed to verify the pathogenicity, and the molecular dynamics simulation method was utilized to assess the impact of this mutation on the activity and structural stability of the OTC protein.ResultsWhole-exome sequencing detected an OTC variant [NM_000531: c.622 (exon6) G > A, p.A208T]. Through comprehensive analysis with various gene mutation prediction tools and in line with the ACMG guidelines, this mutation site was firmly established as a pathogenic site. Moreover, the molecular dynamics simulation results clearly demonstrated that this mutation would significantly compromise the stability of the OTC protein structure.ConclusionThis study deepens our understanding of the clinical manifestations and characteristics of OTCD, especially the OTC A208T gene mutation site. Given the lack of specific clinical manifestations in OTCD patients, early and accurate diagnosis is crucial for effective treatment and prognosis improvement. To our knowledge, this is the first case of this mutation site reported in China.

Summary: Inspired by advancements in natural language processing, we utilize self-supervised learning and an equivariant graph neural network to develop a unified platform for training generative models capable of generating inorganic crystal structures, as well as efficiently adapting to downstream tasks in material property prediction. To mitigate the challenge of evaluating the reliability of generated structures during training, we employ a generative adversarial network (GAN) with its discriminator being a cost-effective reliability evaluator, significantly enhancing model performance. We demonstrate the utility of our model in optimizing crystal structures under predefined conditions. Without external properties acquired experimentally or numerically, our model further displays its capability to help understand inorganic crystal formation by grouping chemically similar elements. This paper extends an invitation to further explore the scientific understanding of material structures through generative models, offering a fresh perspective on the scope and efficacy of machine learning in material science.

Ethephon (ETH) is a plant growth regulator extensively utilized in agriculture, but its overuse is associated with several health issues. However, detecting ETH sensitively and easily in the field is challenging due to the complexity and time-consuming operation of current approaches. In this study, we synthesized aluminum-based metal-organic frameworks (CAU-1) as fluorescent probes for the detection of ETH in fruit. ETH exposure enhanced and shifted the light green fluorescence of CAU-1 to blue through high absorption of phosphate by electrostatic attraction. We observed a linear correlation between fluorescent intensity and ETH concentration ranging from 2 mg/L to 400 mg/L, with the lowest detection limit at 1 mg/L. This fluorescent analysis exhibited good selectivity towards ETH. To facilitate easy identification of samples in the field, we designed a fluorescent paper-based platform with a logic gate operation, allowing visual distinction of samples containing ETH. We applied this platform to monitor ETH in various fruits, including apples, pears, and tomatoes, through fluorescent spectrum, and visual detection. The platform offered simplicity, speed, ease of use and sensitivity, providing a promising future for ETH detection in agriculture.

Abstract The exploration of neural circuitry is paramount for comprehending the computational mechanisms and physiology of the brain. Despite significant advances in materials and fabrication techniques, controlling neuronal connectivity and response in 3D remains a formidable challenge. Here, we introduce a method for engineering the growth of 3D neural circuits with the capability for optical stimulation. We fabricate bioactive interfaces by melt electrospinning writing (MEW) 3D polycaprolactone (PCL) scaffolds followed by coating with titanium carbide (Ti3C2Tx MXene). Beyond enhancing hydrophilicity, cell adhesion, and electrical conductivity, the Ti3C2Tx MXene coating enables optocapacitance-based neuronal stimulation, induced by localized temperature increases upon illumination. This approach offers a pathway for additive manufacturing of neural tissues endowed with optical control, facilitating functional tissue engineering and neural circuit computation.

Abstract Objective The objective of this study was to establish a methodology for determining carboxymethyl lysine (CML) and carboxyethyl lysine (CEL) concentrations in human plasma using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The test results were also used for clinical aging research. Methods Human plasma samples were incubated with aqueous perfluorovaleric acid (NFPA), succeeded by precipitation utilizing trichloroacetic acid, hydrolysis facilitated by hydrochloric acid, nitrogen drying, and ultimate re-dissolution utilizing NFPA, followed by filtration. Cotinine-D3 was added as an internal standard. The separation was performed on an Agela Venusil ASB C18 column (50 mm × 4.6 mm, 5 μm) with a 5 mmol/L NFPA and acetonitrile/water of 60:40 (v/v) containing 0.15% formic acid. The multiple reaction monitoring mode was used for detecting CML, CEL, and cotinine-D3, with ion pairs m/z 205.2 > 84.1 (for quantitative) and m/z 205.2 > m/z 130.0 for CML, m/z 219.1 > 84.1 (for quantitative) and m/z 219.1 > m/z 130.1 for CEL, and m/z 180.1 > 80.1 for cotinine-D3, respectively. Results The separation of CML and CEL was accomplished within a total analysis time of 6 minutes. The retention times of CML, CEL, and cotinine-D3 were 3.43 minutes, 3.46 minutes, and 4.50 minutes, respectively. The assay exhibited linearity in the concentration range of 0.025–1.500 μmol/L, with a lower limit of quantification of 0.025 μmol/L for both compounds. The relative standard deviations of intra-day and inter-day were both below 9%, and the relative errors were both within the range of ±4%. The average recoveries were 94.24% for CML and 97.89% for CEL. Conclusion The results indicate that the developed methodology is fast, highly sensitive, highly specific, reproducible, and suitable for the rapid detection of CML and CEL in clinical human plasma samples. The outcomes of the clinical research project on aging underscored the important indicative significance of these two indicators for research on human aging.

Intervertebral disc degeneration (IDD) is a common chronic inflammatory degenerative disease that causes lower back pain. However, the underlying mechanisms of IDD remain unclear. Ferroptosis suppressor protein 1 (FSP1) is a newly identified suppressor for ferroptosis. This study aims to investigate the role of FSP1 in IDD. Nucleus pulposus (NP) tissues in humans were collected and NP cells from rats were isolated to detect FSP1 expression pattern. The relationship between FSP1-mediated ferroptosis and apoptosis was identified using FSP1 inhibitor iFSP1. RNA sequencing was utilized to seek downstream molecules and related signaling pathways. Moreover, both exogenous recombinant FSP1 protein and endogenous small interfering RNA were implemented in this study to clarify the role of FSP1 in tumor necrosis factor-alpha (TNFα)-mediated NP cell apoptosis. Ultimately, the underlying mechanisms of FSP1-related signaling pathway in IDD were uncovered both in vitro and in vivo. As a result, FSP1 was up-regulated in human degenerative NP tissues and after TNFα stimulation. FSP1 inhibition by iFSP1 fails to trigger ferroptosis in NP cells while inhibiting TNFα-mediated apoptosis. Further experiments demonstrated that FSP1 was closely related to TNFα-reliant caspase 3 activation and mitochondrial damage. However, the exogenous addition of recombinant protein FSP1 does not induce cell death or intensify the efficacy of TNFα. Mechanically, FSP1 is involved in TNFα-mediated NF-κB signaling activation to accelerate the development of IDD. This study demonstrated that FSP1 promotes IDD through TNFα-reliant NF-κB signaling activation and caspase 3-dependent apoptosis. These findings suggested a novel therapeutic target for the treatment of IDD.

Background: Osteoarthritis (OA) is a common chronic joint disease. This study aimed to investigate possible OA diagnostic biomarkers and to verify their significance in clinical samples. Methods: We exploited three datasets from the Gene Expression Omnibus (GEO) database, serving as the training set. We first determined differentially expressed genes and screened candidate diagnostic biomarkers by applying three machine learning algorithms (Random Forest, Least Absolute Shrinkage and Selection Operator logistic regression, Support Vector Machine-Recursive Feature Elimination). Another GEO dataset was used as the validation set. The test set consisted of RNA-sequenced peripheral blood samples collected from patients and healthy donors. Blood samples and chondrocytes were collected for quantitative real-time PCR to confirm expression levels. Receiver operating characteristic curves were generated for individual and combined biomarkers. Results: In total, 251 DEGs were screened, where B3GALNT1, SCRG1 and ZNF423 were screened by all three algorithms. The area under the curve (AUC) of various biomarkers in our test set did not reach as high as that in public datasets. GRB10 exhibited highest AUC of 0.947 in the training set but 0.691 in our test set, while the favorable combined model comprising B3GALNT1, GRB10, KLF9 and SCRG1 demonstrated an AUC of 0.986 in the training set, 1.000 in the validation set and 0.836 in our test set. Conclusion: We identified a combined model for early diagnosis of OA that includes B3GALNT1, GRB10, KLF9 and SCRG1. This finding offers new avenues for further exploration of mechanisms underlying OA.

The widespread use and subsequent accumulation of florfenicol (FFC), a common antibiotic, through the food chain poses significant risks to aquatic ecosystems and human health, necessitating effective strategies for its removal from water bodies. To solve the challenge, herein, we developed a novel aluminum-based metal–organic framework CAU-1, engineered for the efficient adsorption of FFC. CAU-1 contains the plentiful –NH2 and μ-OH groups with the positively charged on the surface. In the adsorption process, CAU-1 perform hydrogen bonding interactions with FFC’s functional groups (−F, –OH, −Cl, –NH–, and −SO2–). Furthermore, the positively charged surface of CAU-1 enhances FFC adsorption via electrostatic attraction together. FFC adsorption equilibrium on CAU-1 is attained within 180 min with a monolayer adsorption capacity of 386 mg/g at 303 K, surpassing most of the reported adsorbents. The exothermic FFC adsorption process on CAU-1 remains largely unaffected by coexisting ions. Additionally, CAU-1 can be efficiently regenerated using a mixed solution of 0.1 M HCl and ethanol–water as an eluent. This work highlights CAU-1’s potential as an effective adsorbent for FFC removal, emphasizing the importance of tuning or designing surface functional groups on adsorbents to boost their adsorption capabilities.

The advancement of gas sensor technology over the past decades has led to remarkable progress and achievements in pollution control and environmental protection. Compared with other sensing materials, electrospun nanofibers have attracted significant attention, which is mainly due to their unique characteristics, including but not limited to high surface area, easy structure design, facile facility setup, multifunctional properties, etc., making them outstanding candidates for potential applications in this field. This review provides an overview of the applications of electrospun nanofibers in gas sensors, concentrating on carbon monoxide, hydrogen, carbon dioxide, hydrogen sulfide, ammonia, nitrogen oxides, oxygen, and volatile organic compounds. It begins with a brief introduction to sensing materials and the advantages of electrospun nanofibers along with their ongoing research. The principles and progress of electrospinning are then discussed. Afterward, the corresponding properties of electrospun nanofibers in diverse gas sensors are thoroughly reviewed. Finally, a future vision regarding challenges and perspectives in this area is proposed. This review provides an extensive and comprehensive reference to utilize advanced electrospun nanofibers to generate novel sensors, facilitating their performance in high-demand areas.

Abstract The limitations of native collagen, such as thermal stability and solubility in physiological environments, can be improved by applying bioconjugation and synthetic chemistry techniques. However, the exquisite control of the modification site of collagen remains a challenge. In this work, pH-responsive poly(acrylic acid) (PAA) with different chain lengths was attached to the N-terminal α-amino groups of succinylated collagen using a site-specific modification strategy. Additionally, the structure, thermal stability, and pH sensitivity of succinylated collagen were explored. The modification rate of amino groups in the succinylated collagen-PAA bioconjugate (SPSC-PAA) was evaluated by the 2,4,6-trinitrobenzene sulfonic acid assay. The impact of N-terminal modification of PAA and its chain length on the thermal stability of collagen was explored by CD and DSC. These techniques revealed that the thermal stability of SPSC-Col is pH-responsive and closely related to the chain length of grafted PAA. The pH sensitivity of SPSC-PAA was further explored by rheology and turbidity. Subsquently, the critical pH and isoelectric point of SPSC-PAAs were also examined by turbidity and isoelectric point titration, respectively. This work provides a new insight into the N-terminal modification of collagen on its properties. Graphical abstract

Fragrant edible sesame oil is popular for its unique aroma. The aroma of sesame oil is determined by its volatile organic compound (VOC) profile. Sesame oils produced by different techniques could have different VOC profiles. In addition, blending fragrant sesame oil with refined oil could also alter the VOC profile of the final product. Current practices in aroma analysis, such as sensory evaluation and gas chromatography (GC), still face many restraints. Hence, there is a need for alternatives. We present a novel 14-unit multiplexed paper-based colorimetric sensor for fragrant sesame oil VOC analysis. The sensor was designed to visualize the VOC profile as a color “fingerprint”. The sensor was validated with 55 branded sesame oil samples produced by two different techniques, i.e., hot pressing and small milling; the experimental results suggested a processing dependency in color VOC fingerprints. The sensor also demonstrated the potential to detect the change in sesame oil VOC profile due to blending with refined oil, with an estimated limit of detection down to 20% v/v of the refined oil. The colorimetric sensor might be used as a simple, rapid, and cost-effective analytical tool in the production and quality control of fragrant sesame oil.

The loblolly pine (Pinus taeda L.) is one of the most profitable forest species worldwide owing to its quick growth, high wood yields, and strong adaptability. The AP2/ERF gene family plays a widespread role in the physiological processes of plant defense responses and the biosynthesis of metabolites. Nevertheless, there are no reports on this gene family in loblolly pine (P. taeda). In this study, a total of 303 members of the AP2/ERF gene family were identified. Through multiple sequence alignment and phylogenetic analysis, they were classified into four subfamilies, including AP2 (34), RAV (17), ERF (251), and Soloist (1). An analysis of the conservation domains, conserved motifs, and gene structure revealed that every PtAP2/ERF transcription factor (TF) had at least one AP2 domain. While evolutionary conservation was displayed within the same subfamilies, the distribution of conserved domains, conserved motifs, and gene architectures varied between subfamilies. Cis-element analysis revealed abundant light-responsive elements, phytohormone-responsive elements, and stress-responsive elements in the promoter of the PtAP2/ERF genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of potential target genes showed that the AP2/ERF gene family might play a critical role in plant growth and development, the response to environmental stresses, and metabolite biosynthesis. Utilizing quantitative real-time PCR (qRT-PCR), we examined the expression patterns of 10 randomly selected genes from Group IX after 6 h of treatments with mechanical injury, ethephon (Eth), and methyl jasmonate (MeJA). The AP2/ERF gene family in the loblolly pine was systematically analyzed for the first time in this study, offering a theoretical basis for exploring the functions and applications of AP2/ERF genes.

IntroductionInfants born

Abstract Fluorescent dyes that emit in the second near‐infrared (NIR‐II, 1000–3000 nm) region have provided significant advances toward real‐time and high‐resolution imaging of vessel and lymphatic system. However, in vivo NIR‐II tracking of the fate of labeled cells still remains challenging. Here, we develop a shielding unit–donor–acceptor–donor–shielding unit (S‐D‐A‐D‐S) NIR‐II fluorophore (FE‐4ZW) with zwitterionic terminal groups for high‐efficiency cell labeling without using cell‐penetrating peptides, which provides for enhanced non‐invasive in vivo determination of the location of cell migration. The tethering terminal sulfoammonium inner salts are featured with its high affinity for cell membranes, thereby enabling the stable labeling even for fixed cells. The fate of transplanted stem cell and the tumor cell migration along lymphatic system in brain or periphery tissues are clearly monitored by the cell‐internalized FE‐4ZW. We also confirmed that a clinically used surfactant, D‐α‐tocopheryl polyethylene glycol‐1000 succinate, can reduce the liver and spleen uptake of FE‐4ZW. The fluorophore design strategy and cell‐labeling technology reported here open a new realm in the visualization of cell migration and insight into the relocation process, thereby ultimately providing an opportunity to investigate in greater detail of the underlying mechanisms of stem cell therapy and tumor metastasis.

Introduction: According to traditional Chinese veterinary medicine, endometritis is caused by a combination of Qi deficiency, blood stasis, and external evil invasion. Salvia miltiorrhiza is a traditional Chinese medicine that counteracts blood stasis and has additional demonstrated effects in boosting energy and restraining inflammation. Salvia miltiorrhiza has been employed in many traditional Chinese prescriptions that have proven effective in healing clinical dairy cow endometritis.Methods: the in vivo effect of Salvia miltiorrhiza in treating endometritis was evaluated in dairy cows. In addition, bovine endometrial epithelium cell inflammation and rat blood stasis models were employed to demonstrate the crosstalk between energy, blood circulation and inflammation. Network analysis, western blotting, qRT-PCR and ELISA were performed to investigate the molecular mechanism of Salvia miltiorrhiza in endometritis treatment.Results: The results demonstrate that treatment with Salvia miltiorrhiza relieves uterine inflammation, increases blood ATP concentrations, and prolongs blood clotting times. Four of the six Salvia miltiorrhiza main components (SMMCs) (tanshinone IIA, cryptotanshinone, salvianolic acid A and salvianolic acid B) were effective in reversing decreased ATP and increased IL-1β, IL-6, and IL-8 levels in an in vitro endometritis model, indicating their abilities to ameliorate the negative energy balance and external evil invasion effects of endometritis. Furthermore, in a blood stasis rat model, inflammatory responses were induced in the absence of external infection; and all six SMMCs inhibited thrombin-induced platelet aggregation. Network analysis of SMMC targets predicted that Salvia miltiorrhiza may mediate anti-inflammation via the Toll-like receptor signaling pathway; anti-aggregation via the Platelet activation pathway; and energy balance via the Thermogenesis and AMPK signaling pathways. Multiple molecular targets within these pathways were verified to be inhibited by SMMCs, including P38/ERK-AP1, a key molecular signal that may mediate the crosstalk between inflammation, energy deficiency and blood stasis.Conclusion: These results provide mechanistic understanding of the therapeutic effect of Salvia miltiorrhiza for endometritis achieved through Qi deficiency, blood stasis, and external evil invasion.

Abstract Skin wound healing often leads to scar formation, presenting physical and psychological challenges for patients. Advancements in messenger RNA (mRNA) modifications offer a potential solution for pulsatile cytokine delivery to create a favorable wound‐healing microenvironment, thereby preventing cutaneous fibrosis. This study aimed to investigate the effectiveness of human adipose‐derived stem cells (hADSCs) enriched with N1‐methylpseudouridine (m1ψ) modified transforming growth factor‐β3 (TGF‐β3) and interleukin‐10 (IL‐10) mRNA in promoting scar‐free healing in preclinical models. The results demonstrated that the modified mRNA (modRNA)‐loaded hADSCs efficiently and temporarily secreted TGF‐β3 and IL‐10 proteins. In a dorsal injury model, hADSCs loaded with modRNA TGF‐β3 and IL‐10 exhibited multidimensional therapeutic effects, including improved collagen deposition, extracellular matrix organization, and neovascularization. In vitro experiments confirmed the ability of these cells to markedly inhibit the proliferation and migration of keloid fibroblasts, and reverse the myofibroblast phenotype. Finally, collagen degradation mediated by matrix metalloproteinase upregulation was observed in an ex vivo keloid explant culture model. In conclusion, the synergistic effects of the modRNA TGF‐β3, IL‐10, and hADSCs hold promise for establishing a scar‐free wound‐healing microenvironment, representing a robust foundation for the management of wounds in populations susceptible to scar formation.

Abstract Background In recent years, numerous guidelines and expert consensus have recommended the inclusion of digital technologies and products in cardiac rehabilitation. Digital therapeutics (DTx) is an evidence-based medicine that uses digital means for data collection and monitoring of indicators to control and optimize the treatment, management, and prevention of disease. Objective This study collected and reviewed real-world data and built a model using health economics assessment methods to analyze the potential cost-effectiveness of DTx applied to home-based cardiac rehabilitation for patients with chronic heart failure. From the perspective of medical and health decision-makers, the economic value of DTx is evaluated prospectively to provide the basis and reference for the application decision and promotion of DTx. Methods Markov models were constructed to simulate the outcomes of DTx for home-based cardiac rehabilitation (DT group) compared to conventional home-based cardiac rehabilitation (CH group) in patients with chronic heart failure. The model input parameters were clinical indicators and cost data. Outcome indicators were quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). The robustness of the evaluation methods and results was tested using sensitivity analyses. Clinical indicators, cost data, and health utility values were obtained from real-world data, including clinical study data, published literature, and public website information. Results The Markov model simulated a time span of 10 years, with a cycle set at one month, for 120 cycles. The results showed that the per capita cost of the CH group was 38,442.11 CNY/year, with a QALY of 0.7196 per person per year. The per capita cost of the DT group was 42,300.26 CNY/year, with a QALY of 0.81687 per person per year. The ICER per person was 39,663.5 CNY/QALY each year, which was below the willingness-to-pay threshold of 85,698 CNY (China's GDP per capita in 2022). Conclusions DTx for home-based cardiac rehabilitation is an extremely cost-effective rehabilitation option compared with conventional home-based cardiac rehabilitation. DTx for home-based cardiac rehabilitation is potentially valuable from the perspective of healthcare decision-makers.

Abstract Background High throughput gene expression profiling is a valuable tool in providing insight into the molecular mechanism of human diseases. Hypoxia- and lactate metabolism-related genes (HLMRGs) are fundamentally dysregulated in sepsis and have great predictive potential. Therefore, we attempted to build an HLMRG signature to predict the prognosis of patients with sepsis. Methods Three publicly available transcriptomic profiles of peripheral blood mononuclear cells from patients with sepsis (GSE65682, E-MTAB-4421 and E-MTAB-4451, total n = 850) were included in this study. An HLMRG signature was created by employing Cox regression and least absolute shrinkage and selection operator estimation. The CIBERSORT method was used to analyze the abundances of 22 immune cell subtypes based on transcriptomic data. Metascape was used to investigate pathways related to the HLMRG signature. Results We developed a prognostic signature based on five HLMRGs (ERO1L, SIAH2, TGFA, TGFBI, and THBS1). This classifier successfully discriminated patients with disparate 28-day mortality in the discovery cohort (GSE65682, n = 479), and consistent results were observed in the validation cohort (E-MTAB-4421 plus E-MTAB-4451, n = 371). Estimation of immune infiltration revealed significant associations between the risk score and a subset of immune cells. Enrichment analysis revealed that pathways related to antimicrobial immune responses, leukocyte activation, and cell adhesion and migration were significantly associated with the HLMRG signature. Conclusions Identification of a prognostic signature suggests the critical role of hypoxia and lactate metabolism in the pathophysiology of sepsis. The HLMRG signature can be used as an efficient tool for the risk stratification of patients with sepsis.

This study aimed to explore the response of archaeal communities and antibiotic-resistance genes (ARGs) to ciprofloxacin (CIP, 0.05–40 mg/L) and copper (Cu, 3 mg/L) combined pollution during stress- and post-effect periods in an activated sludge system. With the increase in the CIP concentration, the diversity of archaea decreased, but the richness increased under the stress of 10 mg/L CIP. Under stress and post effects, the change in unknown archaeal community structure was more significant than that of the known archaea. The relative abundance of unknown archaea was significantly reduced with the increase in CIP concentration. Meanwhile, there were certain archaea that belonged to abundant and rare taxa with different resistance and recovery characteristics. Among them, Methanosaeta (49.15–83.66%), Methanoculleus (0.11–0.45%), and Nitrososphaera (0.03–0.36%) were the typical resistant archaea to combined pollution. And the resistance of the abundant taxa to combined pollution was significantly higher than that of the rare taxa. Symbiotic and competitive relationships were observed between the known and the unknown archaea. The interactions of abundant known taxa were mainly symbiotic relationships. While the rare unknown taxa were mainly competitive relationships in the post-effect period. Rare archaea showed an important ecological niche under the stress-effect. Some archaea displayed positive correlation with ARGs and played important roles as potential hosts of ARGs during stress- and post-periods. Methanospirillum, Methanosphaerula, Nitrososphaera and some rare unknown archaea also significantly co-occurred with a large number of ARGs. Overall, this study points out the importance of interactions among known and unknown archaeal communities and ARGs in a wastewater treatment system under the stress of antibiotics and heavy metal combined pollution.

(1) Background: Laizhou Bay is an important aquaculture area in the north of China. Oplegnathus punctatus is one of the species with high economic benefits. In recent years, the water environment of Laizhou Bay has reached a mild eutrophication level, while microorganisms are an important group between the environment and species. In this study, we evaluated alterations in environmental elements, microbial populations, and antibiotic resistance genes (ARGs) along with their interconnections during Oplegnathus punctatus net culture. (2) Methods: A total of 142 samples from various water layers were gathered for metagenome assembly analysis. Mariculture increases the abundance of microorganisms in this culture area and makes the microbial community structure more complex. The change had more significant effects on sediment than on seawater. (3) Results: Certain populations of cyanobacteria and Candidatus Micrarchaecta in seawater, and Actinobacteria and Thaumarchaeota in sediments showed high abundance in the mariculture area. Antibiotic resistance genes in sediments were more sensitive to various environmental factors, especially oxygen solubility and salinity. (4) Conclusions: These findings highlight the complex and dynamic nature of microorganism–environment–ARG interactions, characterized by regional specificity and providing insights for a more rational use of marine resources.

Abstract Chemotherapy remains as the first-choice treatment option for triple-negative breast cancer (TNBC). However, the limited tumor penetration and low cellular internalization efficiency of current nanocarrier-based systems impede the access of anticancer drugs to TNBC with dense stroma and thereby greatly restricts clinical therapeutic efficacy, especially for TNBC bone metastasis. In this work, biomimetic head/hollow tail nanorobots were designed through a site-selective superassembly strategy. We show that nanorobots enable efficient remodeling of the dense tumor stromal microenvironments (TSM) for deep tumor penetration. Furthermore, the self-movement ability and spiky head markedly promote interfacial cellular uptake efficacy, transvascular extravasation, and intratumoral penetration. These nanorobots, which integrate deep tumor penetration, active cellular internalization, near-infrared (NIR) light-responsive release, and photothermal therapy capacities into a single nanodevice efficiently suppress tumor growth in a bone metastasis female mouse model of TNBC and also demonstrate potent antitumor efficacy in three different subcutaneous tumor models.

Abstract Reproductive traits play a vital role in determining the production efficiency of sheep. Maximizing the production is of paramount importance for breeders worldwide due to the growing population. Circular RNAs (circRNAs) act as miRNA sponges by absorbing miRNA activity through miRNA response elements (MREs) and participate in ceRNA regulatory networks (ceRNETs) to regulate mRNA expression. Despite of extensive research on role of circRNAs as miRNA sponges in various species, their specific regulatory roles and mechanism in sheep ovarian tissue are still not well understood. In this study, we performed whole genome sequencing of circRNAs, miRNA and mRNA employing bioinformatic techniques on ovine tissues of two contrasting sheep breeds "Small tail Han (X_LC) and Dolang sheep (D_LC)", which results into identification of 9,878 circRNAs with a total length of 23,522,667 nt and an average length of 2,381.32 nt. Among them, 44 differentially expressed circRNAs (DECs) were identified. Moreover, correlation between miRNA-mRNA and lncRNA-miRNA provided us with to prediction of miRNA binding sites on nine differentially expressed circRNAs and 165 differentially expressed mRNAs using miRanda. miRNA-mRNA and lncRNA-miRNA pairs with negative correlation were selected to determine the ceRNA score along with positively correlated pairs from lncRNA and mRNA network. Integration of ceRNA score and positively correlated pairs exhibit a significant ternary relationship among circRNAs-miRNA-mRNA demonestrated by ceRNA, comprising of 50 regulatory pairs sharring common nodes and predicted potential differentially expressed circRNAs-miRNAs-mRNAs regulatory axis. Based on functional enrichment analysis shortlisted key ceRNA regulatory pairs associated with reproduction including circRNA_3257-novel579_mature-EPHA3, circRNA_8396-novel130_mature-LOC101102473, circRNA_4140- novel34_mature > novel661_mature-KCNK9, and circRNA_8312-novel339_mature-LOC101110545. Furthermore, expression profiling, functional enrichments and qRT-PCR analysis of key target genes infer their implication in reproduction and metabolism. ceRNA target mRNAs evolutionary trajectories, expression profiling, functional enrichments, subcellular localizations following genomic organizations will provide new insights underlying molecular mechanisms of reproduction, and establish a solid foundation for future research. Graphical Abstract Graphical abstract summarizing the scheme of study

Abstract Background Glioma is the most common malignant primary brain tumor and is characterized by a poor prognosis and limited therapeutic options. ISG20 expression is induced by interferons or double-stranded RNA and is associated with poor prognosis in several malignant tumors. Nevertheless, the expression of ISG20 in gliomas, its impact on patient prognosis, and its role in the tumor immune microenvironment have not been fully elucidated. Methods Using bioinformatics, we comprehensively illustrated the potential function of ISG20, its predictive value in stratifying clinical prognosis, and its association with immunological characteristics in gliomas. We also confirmed the expression pattern of ISG20 in glioma patient samples by immunohistochemistry and immunofluorescence staining. Results ISG20 mRNA expression was higher in glioma tissues than in normal tissues. Data-driven results showed that a high level of ISG20 expression predicted an unfavorable clinical outcome in glioma patients, and revealed that ISG20 was possibly expressed on tumor-associated macrophages and was significantly associated with immune regulatory processes, as evidenced by its positive correlation with the infiltration of regulatory immune cells (e.g., M2 macrophages and regulatory T cells), expression of immune checkpoint molecules, and effectiveness of immune checkpoint blockade therapy. Furthermore, immunohistochemistry staining confirmed the enhanced expression of ISG20 in glioma tissues with a higher WHO grade, and immunofluorescence assay verified its cellular localization on M2 macrophages. Conclusions ISG20 is expressed on M2 macrophages, and can serve as a novel indicator for predicting the malignant phenotype and clinical prognosis in glioma patients.

Objective: The study aimed to investigate changes in basal levels of the inhibitory γ-aminobutyric acid (GABA) neurotransmitter in the sensorimotor cortex (SMC) and cortical gyrification in patients with Parkinson’s disease (PD), which could further identify potential imaging biomarkers for PD, particularly in patients with early-onset Parkinson’s disease (EOPD). Method: Fifty patients with PD (EOPD: 10, late-onset Parkinson’s disease [LOPD]: 40) and fifty-two age- and gender-matched healthy controls (HC) underwent GABA-edited 1H MRS of the SMC and high-resolution 3D T1-weighted brain imaging. GABA levels and local gyrification index (LGI) were calculated to assess GABAergic and cortical gyrification deficits in PD. Result: The Pearson correlation coefficients revealed significant negative associations between eight indicators, including GABA/Cr level and local gyrification index (LGI) of specific cortical regions (precentral, postcentral, entorhinal, superiortemporal, posteriorcingulate, cuneus, and transversetemporal cortex), and the likelihood of Parkinson’s disease (r

Background. Long noncoding RNAs (lncRNAs) often facilitate cellular communication via exosomes. However, their specific roles in head and neck squamous cell carcinoma (HNSCC) are not well understood. Methods. We extracted data on exosome-related lncRNAs from exoRBase and collected transcriptional profiles and clinical details for HNSCC from the TCGA database. Data preprocessing and analyses incorporated Tumor Mutation Burden and Microsatellite Instability from Researcher’s Home and drug sensitivity information from Genomics of Drug Sensitivity in Cancer database. We developed a prognostic model using Cox regression and LASSO regression analysis, with subsequent multivariate analysis to identify significant prognostic indicators. We also constructed a nomogram to evaluate the model’s clinical relevance, performed Gene Set Enrichment Analysis (GSEA), and analyzed the immune microenvironment and therapy sensitivity using CIBERSORT and TIDE algorithms. Supporting in vitro experiments and statistical analyses were conducted. Results. Our comprehensive investigation revealed 17 exosome-associated lncRNAs critical for patient survival in HNSCC. This enabled the development of a prognostic model that effectively stratifies patients into high-risk and low-risk categories. These lncRNAs correlate with patient demographics and clinical characteristics such as age, gender, and tumor stage. GSEA highlighted significant gene expression differences between the risk groups, particularly in pathways related to muscle formation, cellular transition, and immune response. The analysis of the immune microenvironment showed distinct immune cell infiltration patterns in high-risk patients, indicative of compromised immune defenses. In addition, we explored the expression of critical immune checkpoints and their impact on immunotherapy efficacy, demonstrating that risk scores may predict treatment responses. Notably, LINC01564 was overexpressed in HNSCC, associated with poorer prognosis, enhanced xenobiotic metabolism, and altered immune cell infiltration. Experimental validation confirmed LINC01564’s role in promoting tumor cell proliferation, invasion, and migration, highlighting its therapeutic potential. Conclusions. Our study highlights the importance of exosome-associated lncRNAs in HNSCC, identifying 17 critical lncRNAs as vital prognostic markers. The upregulation of LINC01564, associated with poor outcomes and increased tumor aggressiveness, underscores its potential as a therapeutic target.

Background and purposeFavorable wall apposition of a flow diverter (FD) is essential for the treatment of intracranial aneurysms. The irretrievability and final drop point uncertainty of the proximal tail of the FD increase the difficulty of achieving good tail apposition. Therefore, understanding the factors associated with FD tail malapposition would be helpful for clinical practice.MethodsA total of 153 patients with 161 FD deployments in the carotid artery between 2020 and 2023 were retrospectively collected from our center’s database for this study. Patient demographics, aneurysm characteristics, FDs, carotid artery anatomy, periprocedural complications, discharge modified Rankin scale (MRS) scores, and follow-up outcomes were investigated by comparing patients with and without FD tail malapposition. Comparisons were made with t tests or Kruskal–Wallis tests for continuous variables and the Pearson χ2 or Fisher exact test for categorical variables. Logistic regression was conducted to determine the predictors of malapposition.ResultsTail malapposition occurred for 41 out of the 161 FDs (25.5%). Univariate analysis revealed that the FD brand, FD length, FD distal to proximal vessel diameter ratio, FD tail position (straight or curved), and curvature of the vessel curve were significantly associated with FD tail malapposition (p

Background In recent years, numerous guidelines and expert consensuses have recommended that digital technologies and products, such as digital therapeutics (DTx), be incorporated into cardiac rehabilitation (CR). Objective The study aims to compare the cost-effectiveness of DTx for home-based CR (HBCR) with that of the conventional HBCR for patients with atrial fibrillation (AF) after catheter ablation in a real-world clinical setting. Methods Based on a single-center, prospective, blinded, randomized, parallel controlled trial of DTx-based HBCR for AF patients after catheter ablation, 100 AF patients undergoing catheter ablation were selected and randomized at a 1:1 ratio into a UC group (conventional HBCR) and DT group (DTx-based HBCR). The intervention lasted for 12 weeks. Medical cost data and clinical efficacy data (VO 2 max) were acquired from trial data. Effect data (QALYs, anxiety and depression status, health beliefs related to cardiovascular disease, and exercise self-efficacy) were obtained from a patient questionnaire. The cost-effectiveness analysis was conducted to assess the economic benefits of DTx-based HBCR versus conventional HBCR, and the robustness of the results was verified by sensitivity analysis. Results In the DT group (n = 49), the mean QALYs increased 0.119 ± 0.09, VO 2 max increased 9.3 ± 8.0 mL/(min*kg), anxiety, depression, health belief, and exercise self-efficacy had improved, and the total medical cost was 75,080.55 ± 19,746.62 CNY. In the UC group (n = 48), the mean QALYs increased 0.077 ± 0.06, VO 2 max increased 4.9 ± 6.6 mL/(min*kg), anxiety, depression, health belief, and exercise self-efficacy had improved, and the total medical cost was 73,972.66 ± 16,582.04 CNY. The difference in the medical cost was 1107.89 CNY, and the incremental cost-effectiveness ratio was 33,572.42 CNY/QALY, which was lower than the willingness-to-pay threshold of 85,698 CNY (China's per capita GDP in 2022). Conclusion DTx-based HBCR is more effective and cost-effective than conventional HBCR.

Purpose: This study aimed to screen biomarkers to predict the efficacy of programmed cell death 1 (PD-1) blockade immunotherapy combined with chemotherapy as neoadjuvant therapy for esophageal squamous cell carcinoma (ESCC). Methods: In the first stage of the study, the baseline concentrations of 40 tumor-related chemokines in the serum samples of 50 patients were measured to screen for possible biomarkers. We investigated whether the baseline concentration of the selected chemokine was related to the therapeutic outcomes and tumor microenvironment states of patients treated with the therapy. In the second stage, the reliability of the selected biomarkers was retested in 34 patients. Results: The baseline concentration of macrophage migration inhibitory factor (MIF) was negatively correlated with disease-free survival (DFS) and overall survival (OS) in patients treated with the therapy. In addition, a low baseline expression level of MIF is related to a better tumor microenvironment for the treatment of ESCC. A secondary finding was that effective treatment decreased the serum concentration of MIF. Conclusion: Baseline MIF levels were negatively correlated with neoadjuvant therapy efficacy. Thus, MIF may serve as a predictive biomarker for this therapy. The accuracy of the prediction could be improved if the serum concentration of MIF is measured again after the patient received several weeks of treatment.

The demand for CO2 detection steadily increases mainly due to the greenhouse effect caused by CO2 emission, which significantly impacts the environment. Among different promising candidates, carbon-based (i.e., graphene, carbon nanotubes, carbon nanoparticles, etc.) composites have been widely studied due to their exceptional mechanical, electrical, and thermal properties. Carbon-based composites also offer high strength-to-weight ratios, excellent conductivity, and superior thermal stability, making them ideal materials for various industrial applications. Despite tremendous efforts to develop CO2 sensors from these materials, obtaining a well-dispersed system that is affordable and easy to use remains challenging. In this work, we have demonstrated a low-cost and effective chemiresistive CO2 sensor based on a composite of functionalized carbon nanotubes (f-CNTs) with polyethyleneimine (PEI). When modified with pyrene and chlorosulfonic acid, the resultant f-CNTs have outstanding dispersibility in PEI, which is mainly attributed to the non-covalent bonds between the CNTs and pyrene and the interaction between the amine and sulfonate groups. The rheology of the f-CNT/PEI composites has been thoroughly studied, which tremendously influences the screen-printing quality. The resulting sensor shows excellent selectivity and sensitivity, which can respond to the CO2 concentration in a wide range of 300 - 5000 ppm. The effects of ink dilution and humidity from the environment on the sensor performance have also been further explored. More importantly, the working mechanism has been proposed, and we hope it can provide insight and a new pathway for future sensor design.

Abstract circRNAs, as miRNA sponges, participate in many important biological processes. However, it remains unclear whether circRNAs can regulate lipid metabolism. This study aimed to explore the competing endogenouse RNA (ceRNA) regulatory network that affects the difference between intramuscular fat (IMF) and subcutaneous fat (SCF) deposition, and to screen key circRNAs and their regulatory genes. In this experiment, we identified 265 differentially expressed circRNAs, of which 187 up-regulated circRNA and 78 down-regulated circRNA in IMF. Subsequently, we annotated the function of DEcircRNA's host genes, and found that DEcircRNA's host genes were mainly involved in GO terms (including cellular response to fatty acids, lysophosphatidic acid acyltransferase activity, R-SMAD binding, etc.) and signaling pathways (fatty acid biosynthesis, Citrate cycle, TGF- β Signal pathway) related to adipogenesis, differentiation and lipid metabolism. By constructing a circRNA-miRNA network, we screened out DEcircRNA that can competitively bind to more miRNAs as key circRNAs (circRNA_06424 and circRNA_08840). Through the functional annotation of indirect target genes and protein network analysis, we found that circRNA_06424 affects the expression of PPARD, MMP9, UBA7 and other indirect target genes by competitively binding to miRNAs such as ssc-miR-339-5p, ssc-miR-744 and ssc-miR-328, and participates in PPAR signaling pathway, Wnt signaling pathway, unsaturated fatty acid and other signaling pathways, resulting in the difference of fat deposition between IMF and SCF. This study provide a theoretical basis for further research investigating the differences of lipid metabolism in different adipose tissues, providing potential therapeutic targets for ectopic fat deposition and lipid metabolism diseases.

Abstract Background Increasing evidences have revealed the tumor immune microenvironment not only has vital impacts on the origin, progression, and metastasis of tumors significantly but also influences the response to immunotherapy. Nonetheless, to date, the well-rounded expression pattern of immune-related genes in cutaneous melanoma and the comprehensive characterization of tumor immune microenvironment remain not clearly elucidated. Method We comprehensively evaluated the well-rounded expression pattern of immune-related genes of 686 patients with cutaneous melanoma based on immune-related genes with prognostic value and systematically correlated the expression pattern of these genes with the comprehensive characterization of tumor immune microenvironment. The IRGscore was constructed to quantify immunological function of individual using principal component analysis algorithms. Result Three distinct immune subtypes were determined with obvious survival differences. Melanoma patients with high IRGscore was characterized by comprehensive suppression of immune function, showing much poorer prognosis and efficacy for immunotherapy, while the low IRGscore means the robust activation of immune function and the better effect of immunotherapy, which may be responsible for a better prognosis. Besides, the prognostic ability of IRGscore was further validated by the independent dataset of stomach cancers. Furthermore, the predictive effect of immunotherapeutic benefits of IRGscore was demonstrated by the independent dataset of melanoma patients accepting immunotherapy and another predictive model for immunotherapy. Conclusion IRGscore could serve as an independent immunotherapeutic and prognostic predictor, thereby facilitating the identification of appropriate candidates with cutaneous melanoma for immunotherapy and the formulation of individualized therapeutic approaches.

Sonogenetics refers to the use of genetically encoded, ultrasound-responsive mediators for noninvasive and selective control of neural activity. It is a promising tool for studying neural circuits. However, due to its infancy, basic studies and developments are still underway, including gauging key in vivo performance metrics such as spatiotemporal resolution, selectivity, specificity, and safety. In this paper, we summarize recent findings on sonogenetics to highlight technical hurdles that have been cleared, challenges that remain, and future directions for optimization.

Microglial reaction plays a key role in the prognosis of traumatic CNS injuries (TBI and SCI). A growing number of studies have shown that mesenchymal stem cells (MSCs) play an important role in regulating microglial states. This review summarizes the effects and mechanisms of different sources of MSCs on microglial states in the last 5 years. In general, bone marrow-derived mesenchymal stem cells are the most accessible and widely used, and can produce immunosuppressive effects on a variety of brain injuries including TBI through tissue engineering in situ implantation; MSCs mainly regulate inflammatory pathways and promote the states of microglia in the anti-inflammatory direction, which also secrete certain cytokines or extracellular vesicles to affect apoptotic pathways, such as the extracellular vesicles miR-21-5p, acting as a neuronal protector.

IntroductionPinus elliottii × P. caribaea is one of the major tree species in commercial forest bases in developed countries. However, in the process of sapling cultivation, nutrients cannot be accurately detected and supplied to individual saplings, resulting in reduced yield and quality.MethodsIn this paper, visible-near-infrared (Vis-NIR) hyperspectral imaging (HSI) combined with ensemble learning (EL) was used to solve this problem. The content and distribution of nitrogen (N), phosphorus (P), and potassium (K) in the canopy needles of Pinus elliottii × P. caribaea saplings were obtained through HSI data analysis, and the nutritional needs of individual plants were reflected to provide a basis for nutritional supply decisions. The saplings were treated with deficient, sufficient, and excessive N, P, and K single-element fertilizers. After collecting the Vis-NIR hyperspectral images of these saplings, a variety of pre-processing, feature selection, and ensemble learning algorithms were used to establish predictive models. The R2 and RMSE were used to evaluate the performance of the prediction models.ResultsThe results showed that the multiple scattering correction-competitive adaptive reweighted sampling-Stacking (MSC-CARS-Stacking) model had the best results among the three nutrient elements prediction models (Rp2-N = 0.833, RMSEP = 0.380; Rp2-P = 0.622, RMSEP = 0.101; Rp2-K = 0.697, RMSEP = 0.523). When studying the sensitive bands of N, P, and K, we found that the common characteristic wavelengths were 675.3 and 923.9 nm, while the non-common characteristic wavelengths were located at 550 nm (green peak), 680 nm (red valley), and 960 nm (water peak). In studying the generalization ability of the model, only the nitrogen group data were used to train the MSC-CARS-Stacking model for nitrogen prediction, which was then used to predict the nitrogen content in the phosphorus and potassium groups, obtaining good results (Rc2-N = 0.841, Rp2-P = 0.814, Rp2-K = 0.801). It showed a strong generalization ability for the prediction of nitrogen, and similarly, phosphorus and potassium.DiscussionIn conclusion, this study verifies that the Vis-NIR HSI combined with EL is indeed a reliable and stable method to predict the contents of N, P, and K in the needles of Pinus elliottii × P. caribaea sapling canopy.

Summary: The immune-genetic changes that occur in cancer patients experiencing hyperprogressive disease (HPD) during combined immunotherapy are unclear. In this study, HPD patients with pre- and post-HPD samples and non-HPD patients with solid tumors were molecularly characterized by genetic and tumor immune microenvironment (TiME) analyses of paired samples by whole-exome sequencing, RNA sequencing, and multiplex immunofluorescence. The genetic analysis of paired samples showed that almost all the tumor driver gene mutations were preserved between pre- and post-HPD tumors. HPD patients had higher frequencies of mutations in TP53 and CNN2, and a significantly higher mutant-allele tumor heterogeneity than non-HPD patients. Tumor IL-6 mRNA was upregulated in post-HPD samples vs. pre-HPD, accompanied by a potential immune suppressive TiME with an elevated M2/M1 ratio. Salvage treatment with irinotecan plus bevacizumab was effective in one HPD patient, who experienced prolonged survival. These genetic features and TiME characteristics might help identify the features of HPD after immunotherapy.

Abstract Background This study intended to clarify the mechanisms by which WISP1-mediated IGF1/αvβ3/Wnt axis might affect the progression of ovarian cancer. Methods Bioinformatics analysis was implemented for pinpointing expression of IGF1 and WISP1 which was verified through expression determination in clinical tissue samples and cells. Next, gain- or loss-of-function experimentations were implemented for testing CAOV4 and SKOV3 cell biological processes. The interaction between WISP1 and IGF1 was verified by co-immunoprecipitation and the molecular mechanism was analyzed. Finally, ovarian cancer nude mouse models were prepared to unveil the in vivo effects of WISP1/IGF1. Results IGF1 and WISP1 expression was elevated in ovarian cancer tissues and cells, which shared correlation with poor prognosis of ovarian cancer sufferers. Elevated IGF1 induced malignant properties of ovarian cancer cells through activation of PI3K-Akt and Wnt signaling pathway. WISP1 was positively correlated with IGF1. WISP1 could enhance the interaction between IGF1 and αvβ3 to induce epithelial-mesenchymal transition. In vivo experiments also confirmed that upregulated WISP1/IGF1 induced tumorigenesis and metastasis of ovarian cancer cells. Conclusion In conclusion, WISP1 can facilitate ovarian cancer by activating Wnt via the interaction between IGF1 and αvβ3.

Abstract The function of long non-coding RNA (lncRNA) can be achieved through the regulation of target genes, and the deposition of fat is regulated by lncRNA. Fat has an important effect on meat quality. However, there are relatively few studies on lncRNAs in the subcutaneous adipose tissue of Duolang sheep and Small Tail Han sheep. In this study, RNA-Seq technology and bioinformatics methods were used to identify and analyze the lncRNA and mRNA in the subcutaneous adipose tissue of the two breeds of sheep. The results showed that 107 lnRNAs and 1329 mRNAs were differentially expressed. The differentially expressed genes and lncRNA target genes were significantly enriched in the biosynthesis of unsaturated fatty acids signaling pathway, fatty acid metabolism, adipocyte differentiation and other processes related to fat deposition. Among them, LOC105616076, LOC114118103, LOC105607837, LOC101116622, and LOC105603235 target FADS1, SCD, ELOVL6, HSD17B12 and HACD2, respectively. They play a key regulatory role in the biosynthesis of unsaturated fatty acids. This study lays a foundation for the study of the molecular mechanism of lncRNA on fat development, and has reference value for studying the differences in fat deposition between Duolang sheep and Small Tail Han sheep.

IntroductionPneumonia-induced sepsis can cause multiple organ dysfunction including acute lung and kidney injury (ALI and AKI). Surfactant protein A (SP-A), a critical innate immune molecule, is expressed in the lung and kidney. Extracellular vesicles like exosomes are involved in the processes of pathophysiology. Here we tested one hypothesis that SP-A regulates pneumonia-induced AKI through the modulation of exosomes and cell death.MethodsWild-type (WT), SP-A knockout (KO), and humanized SP-A transgenic (hTG, lung-specific SP-A expression) mice were used in this study.ResultsAfter intratracheal infection with Pseudomonas aeruginosa, KO mice showed increased mortality, higher injury scores, more severe inflammation in the lung and kidney, and increased serum TNF-α, IL-1β, and IL-6 levels compared to WT and hTG mice. Infected hTG mice exhibited similar lung injury but more severe kidney injury than infected WT mice. Increased renal tubular apoptosis and pyroptosis in the kidney of KO mice were found when compared with WT and hTG mice. We found that serum exosomes from septic mice cause ALI and AKI through mediating apoptosis and proptosis when mice were injected intravenously. Furthermore, primary proximal tubular epithelial cells isolated from KO mice showed more sensitivity than those from WT mice after exposure to septic serum exosomes.DiscussionCollectively, SP-A attenuates pneumonia-induced ALI and AKI by regulating inflammation, apoptosis and pyroptosis; serum exosomes are important mediators in the pathogenesis of AKI.

Osteoarthritis (OA), viewing as a degenerative aseptic inflammatory disease, is characterized by joint pain and inflammation that significantly affects the quality of patients’ life, especially for the elder. Although rapid progress has been achieved in elucidating the underlying mechanisms of OA occurrence and progression, there is still a lack of effective clinical therapeutics for OA patients. Currently the most common treatments including drug therapy and surgical operations are not very satisfactory in majority of cases, so it is worthy to explore new remedies. During the past few decades, a number of novel forms of regulated cell death have been reported widely, typified by ferroptosis, with its prominent features including reactive oxygen species (ROS) elevation, lipid peroxidation, iron accumulation and glutathione deprivation. Our study was designed to identify the functional roles of differentially expressed ferroptosis-related genes in OA, which were screened out by referring to GEO database via bioinformatics analyses. Human chondrocytes were applied to validate the above findings in the scenario of ferroptosis inhibitors administration. Results partially proved the consistency with bioinformatics analyses that ATF3 and TFRC were highly expressed in interleukin-1β (IL-1β)-stimulated chondrocytes whereas CXCL2 and JUN were downregulated. Besides, TFRC was firstly validated to be upregulated in IL-1β-stimulated chondrocytes, which could be reversed by ferroptosis inhibitors. In conclusion, our study reported two prominent ferroptosis-related genes, ATF3 and TFRC are upregulated in IL-1β-stimulated chondrocytes while CXCL2 and JUN are downregulated. And preliminary results demonstrated that TFRC might serve as an accomplice of ferroptosis process in IL-1β-stimulated chondrocytes and ferroptosis inhibitors have the potential to inhibit ROS in IL-1β-stimulated chondrocytes.

Interactive machine learning (IML) aims to make machine learning an easy-to-use tool for novice users to solve personalized tasks. However, despite the recent popularity of edge AI, research into interactive machine learning on edge devices has not been conducted actively. Existing IML designs cannot be directly applied to small edge devices due to interface and computational resource limitations. In this paper, we propose a method for efficient model personalization on a small interactive object recognition camera device by combining sample recommendations with an IML workflow. The proposed method recommends training data candidates from unlabeled samples in addition to the usual annotation operations. Our method interactively trains a noise filter to handle a noisy sample pool obtained while using the device. The user can indicate whether the recommended sample corresponds to 1) the recommended class; 2) other classes; or 3) noise unrelated to the recognition task by providing ternary feedback. Our system is designed to gradually update both the target classifier and the noise filtering recommendation modules on the basis of feedback. We show that our feedback design achieves more efficient model training while improving system usability through a systematic evaluation and user study using a prototype device.