The combination of breast cancer PDO and mini-PDX platform for drug screening and individualized treatment.

The majority of advanced breast cancers exhibit strong aggressiveness, heterogeneity, and drug resistance, and currently, the lack of effective treatment strategies is one of the main challenges that cancer research must face. Therefore, developing a feasible preclinical model to explore tailored treatments for refractory breast cancer is urgently needed. We established organoid biobanks from 17 patients with breast cancer and characterized them by immunohistochemistry (IHC) and next generation sequencing (NGS). In addition, we in the first combination of patient-derived organoids (PDOs) with mini-patient-derived xenografts (Mini-PDXs) for the rapid and precise screening of drug sensitivity. We confirmed that breast cancer organoids are a high-fidelity three-dimension (3D) model in vitro that recapitulates the original tumour's histological and genetic features. In addition, for a heavily pretreated patient with advanced drug-resistant breast cancer, we combined PDO and Mini-PDX models to identify potentially effective combinations of therapeutic agents for this patient who were alpelisib + fulvestrant. In the drug sensitivity experiment of organoids, we observed changes in the PI3K/AKT/mTOR signalling axis and oestrogen receptor (ER) protein expression levels, which further verified the reliability of the screening results. Our study demonstrates that the PDO combined with mini-PDX model offers a rapid and precise drug screening platform that holds promise for personalized medicine, improving patient outcomes and addressing the urgent need for effective therapies in advanced breast cancer.

Supramolecular channels via crown ether functionalized polyaniline for proton-self-doped cathode in aqueous zinc-ion battery.

Polyaniline (PANI) has been widely used as a cathode in aqueous zinc-ion batteries (AZIBs) because of its attractive conductivity and energy storage capability. However, the extensive application of PANI is limited by spontaneous deprotonation and slow diffusion kinetics. Herein, an 18-crown-6-functionalised PANI pseudorotaxane (18C6@PANI) cathode is successfully developed through a facile template-directed polymerisation reaction. The 18C6@PANI cathode exhibits a high specific capacity of 256 mAh g-1 at 0.2 A/g, excellent rate performance of 134 mAh g-1 at 6 A/g and outstanding cycle stability at a high current density of 3 A/g over 10,000 cycles. Experimental and theoretical analyses demonstrate the formation of the -N-Zn-O- structure. The abundant supramolecular channels in pseudorotaxane, induced by crown ether functional groups, are beneficial for achieving superior cyclability and rate capability. These encouraging results highlight the potential for designing more efficient PANI-based cathodes for high-performance AZIBs.

Integrated metabolomic and transcriptomic analysis of triterpenoid accumulation in the roots of Codonopsis pilosula var. modesta (Nannf.) L.T.Shen at different altitudes.

INTRODUCTION: Codonopsis Radix is a beneficial traditional Chinese medicine, and triterpenoid are the major bioactive constituents. Codonopsis pilosula var. modesta (Nannf.) L.T.Shen (CPM) is a precious variety of Codonopsis Radix, which is distributed at high mountain areas. The environment plays an important role in the synthesis and metabolism of active ingredients in medicinal plants, but there is no report elaborating on the effect of altitude on terpenoid metabolites accumulation in CPM. OBJECTIVES: This study aims to analyse the effects of altitude on triterpenoid biosynthetic pathways and secondary metabolite accumulation in CPM. MATERIAL AND METHODS: The untargeted metabolomics based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) and 10 triterpenoids based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) method were analysed at the low-altitude (1480 m) and high-altitude (2300 m) CPM fresh roots. The transcriptome based on high-throughput sequencing technology were combined to analyse the different altitude CPM triterpenoid biosynthetic pathways. RESULTS: A total of 17,351 differentially expressed genes (DEGs) and 55 differentially accumulated metabolites (DAMs) were detected from the different altitude CPM, and there are significant differences in the content of the 10 triterpenoids. The results of transcriptome study showed that CPM could significantly up-regulate the gene expression levels of seven key enzymes in the triterpenoid biosynthetic pathway. CONCLUSIONS: The CPM at high altitude is more likely to accumulate triterpenes than those at low altitude, which was related to the up-regulation of the gene expression levels of seven key enzymes. These results expand our understanding of how altitude affects plant metabolite biosynthesis.

An eco-friendly porous hydrogel adsorbent based on dextran/phosphate/amino for efficient removal of Be(II) from aqueous solution.

A novel environmentally-friendly porous hydrogel adsorbent (GHPN) is firstly designed and prepared using dextran, phosphate, and calcium hydroxide for the adsorption of Be(II). GHPN shows good adsorption selectivity for Be(II) (Kd = 1.53 × 104 mL/g). According the adsorption kinetics and thermodynamics, the theoretical adsorption capacity of GHPN to Be(II) is 43.75 mg/g (35 °C, pH = 6.5), indicating a spontaneous exothermic reaction. After being reused for 5 cycles, the adsorption and desorption efficiencies of Be(II) with GHPN are obtained to be more than 80 %, showing acceptable recycling performance. Both of the characterizations and theoretical calculations indicate that the phosphate group, hydroxyl group, and amino group own the affinity to form stable complexes with Be(II). Benefiting from the introduction of phosphate and amino, the adsorption effect of the hydrogel adsorbent on Be(II) can be greatly improved, and surface precipitation, complexation, and ligand exchange are the dominant mechanisms of beryllium adsorption. The results suggest that GHPN has great potential to be utilized as an eco-friendly and useful adsorbent of Be(II) from aqueous solution.

Next-generation anti-PD-L1/IL-15 immunocytokine elicits superior antitumor immunity in cold tumors with minimal toxicity.

The clinical applications of immunocytokines are severely restricted by dose-limiting toxicities. To address this challenge, here we propose a next-generation immunocytokine concept involving the design of LH05, a tumor-conditional anti-PD-L1/interleukin-15 (IL-15) prodrug. LH05 innovatively masks IL-15 with steric hindrance, mitigating the "cytokine sink" effect of IL-15 and reducing systemic toxicities associated with wild-type anti-PD-L1/IL-15. Moreover, upon specific proteolytic cleavage within the tumor microenvironment, LH05 releases an active IL-15 superagonist, exerting potent antitumor effects. Mechanistically, the antitumor efficacy of LH05 depends on the increased infiltration of CD8+ T and natural killer cells by stimulating the chemokines CXCL9 and CXCL10, thereby converting cold tumors into hot tumors. Additionally, the tumor-conditional anti-PD-L1/IL-15 can synergize with an oncolytic virus or checkpoint blockade in advanced and metastatic tumor models. Our findings provide a compelling proof of concept for the development of next-generation immunocytokines, contributing significantly to current knowledge and strategies of immunotherapy.

Integrated molybdenum single atom array sensors with multichannels for nitrite detection in foods.

Nitrite (NO2-) is present in a variety of foods, but the excessive intake of NO2- can indirectly lead to carcinogenic, teratogenic, mutagenicity and other risks to the human body. Therefore, the detection of NO2- is crucial for maintaining human health. In this study, an integrated array sensor for NO2- detection is developed based on molybdenum single atom material (IMSMo-SAC) using high-resolution electrohydrodynamic (EHD) printing technology. The sensor comprises three components: a printed electrode array, multichannels designed on polydimethylsiloxane (PDMS) and an electronic signal process device with bluetooth. By utilizing Mo-SAC to facilitate electron transfer during the redox reaction, rapid and efficient detection of NO2- can be achieved. The sensor has a wide linear range of 0.1 µM-107.8 mM, a low detection limit of 33 nM and a high sensitivity of 0.637 mA-1mM-1 cm-2. Furthermore, employing this portable array sensor allows simultaneously measurements of NO2- concentrations in six different foods samples with acceptable recovery rates. This array sensor holds great potential for detecting of small molecules in various fields.

Clinimetric properties of the "FIND-NEEDS" to screen geriatric conditions.

INTRODUCTION: Comprehensive geriatric assessment (CGA) is used to thoroughly assess and identify complex healthcare problems among older adults. However, administration of CGA is time-consuming and labor intensive. A simple screening tool with the mnemonic "FIND-NEEDS" was developed to quickly identify common geriatric conditions. The present study was to evaluate the clinimetric properties of the FIND-NEEDS. METHODS: First-visiting older adults aged 65 years and above (and who were able to communicate by themselves or with the help of a caregiver) were assessed (October to December, 2021) using the FIND-NEEDS and CGA at geriatric outpatient clinics of a tertiary, referred medical center. The FIND-NEEDS was examined for its criterion-related validity and compared with the CGA results. Two types of scoring (summed score and binary score) of FIND-NEEDS and CGA were analyzed using Spearman correlation, sensitivity and specificity, and area under receiver operating characteristic curve (AUC). RESULTS: The mean age of the 114 outpatients was 78.3±7.6 years, and 79(69.3%) were female. The internal consistency was excellent when using all FIND-NEEDS items, and was acceptable when using domain scores. Exploratory factor analysis showed that most of the FIND-NEEDS domain scores had factor loadings higher than 0.3. Intercorrelations of binary scores between domains of FIND-NEEDS and CGA showed most domains were moderately correlated. The overall correlation of summed scores between FIND-NEEDS and CGA was high. The FIND-NEEDS summed score was moderately correlated with CGA score (r=0.494; p<0.001), and the binary score showed excellent correlation (r=0.944; p<0.001). When using the CGA score as the gold standard, the FIND-NEEDS showed excellent AUC (0.950), sensitivity (1.00), and specificity (0.90). DISCUSSION/CONCLUSION: The present study demonstrated that the FIND-NEEDS had acceptable clinimetric properties to screen for geriatric problems among older adults. Further in-depth assessment and care plan can then be conducted afterwards.

Modeling refined differences of cortical folding patterns via spatial, morphological, and temporal fusion representations.

The gyrus, a pivotal cortical folding pattern, is essential for integrating brain structure-function. This study focuses on 2-Hinge and 3-Hinge folds, characterized by the gyral convergence from various directions. Existing voxel-level studies may not adequately capture the precise spatial relationships within cortical folding patterns, especially when relying solely on local cortical characteristics due to their variable shapes and homogeneous frequency-specific features. To overcome these challenges, we introduced a novel model that combines spatial distribution, morphological structure, and functional magnetic resonance imaging data. We utilized spatio-morphological residual representations to enhance and extract subtle variations in cortical spatial distribution and morphological structure during blood oxygenation, integrating these with functional magnetic resonance imaging embeddings using self-attention for spatio-morphological-temporal representations. Testing these representations for identifying cortical folding patterns, including sulci, gyri, 2-Hinge, and 2-Hinge folds, and evaluating the impact of phenotypic data (e.g. stimulus) on recognition, our experimental results demonstrate the model's superior performance, revealing significant differences in cortical folding patterns under various stimulus. These differences are also evident in the characteristics of sulci and gyri folds between genders, with 3-Hinge showing more variations. Our findings indicate that our representations of cortical folding patterns could serve as biomarkers for understanding brain structure-function correlations.

Resonance of fatty acid metabolism and immune infiltration in anti-PD-1 monotherapy for breast cancer.

The interaction between tumor fatty acid metabolism and immune microenvironment is a novel topic in oncology research, and the relationship of lipid-derived factors with immune editing in tumor is unclear. The breast cancer samples from the TCGA database were used as the training set, and samples from GSE42568 were employed as the validation set for constructing a model to identify a signature associated with fatty acid metabolism through Lasso Cox regression. And the changes in immune related signatures and risk score before and after anti-PD-1 monotherapy were caught by the differential analysis in GSE225078. A 14-gene prognostic risk scoring model identifying by fatty acid metabolism relevant signature was conducted, and the high risk group had shorter overall survival and progression free survival than low risk group. Many metabolism-related pathways were enriched in the high risk group, and many immune-related pathways were enriched in low risk group. The crucial differentially expressed genes between the high/low risk groups, CYP4F8 and CD52, were found to be strongly associated with SUCLA2 and ACOT4 of 14-gene model, and strongly related to immune infiltration. Immune related signatures, fatty acid metabolism-risk score and the expression level of ALDH1A1 (in 14-gene-model) changed after anti-PD-1 monotherapy. And the mice model results also showed anti-PD-1 mAb could significantly reduce the expression level of ALDH1A1 (p < 0.01). These results brought up the crosstalk between immune components and fatty acid metabolism in breast cancer microenvironment, which provided a new possibility of targeting fatty acid metabolism for combination therapy in breast cancer immunotherapy.

Microbial-induced carbonate precipitation effectively prevents Pb2+ migration through the soil profile: Lab experiment and model simulation.

Due to the inappropriate disposal of waste materials containing lead (Pb) and irrigation with sewage containing Pb, the migration of Pb2+ within the soil profile has been extensively investigated. The conventional Pb2+ block method is challenging to implement due to its complex operational procedures and high construction costs. To address this issue, this study introduces the microbial-induced carbonate precipitation (MICP) technique as a novel approach to impede the migration of Pb2+ in the soil profile. Soil acclimatization with urea resulted in an increased proportion of urease-producing microorganisms, including Bacillus, Paenibacillus, and Planococcaceae, along with heightened expression of urea-hydrolyzing genes (UreA, UreB, UreC, and UreG). This indicates that urea-acclimatized soil (Soil-MICP) possesses the potential to induce carbonate precipitation. Batch Pb2+ fixation experiments confirmed that the fixation efficiency of Soil-MICP on Pb2+ exceeded that of soil without MICP, attributed to the MICP process within the Soil-MICP group. Dynamic migration experiments revealed that the MICP reaction transformed exchangeable lead into carbonate-bound Pb, effectively impeding Pb2+ migration in the soil profile. Additionally, the migration rate of Pb2+ in Soil-MICP was influenced by varying urea amounts, pH levels, and pore flow rates, leading to a slowdown in migration. The Two-site sorption model aptly described the Pb2+ migration process in the Soil-MICP column. This study aims to elucidate the MICP biomineralization process, uncover the in-situ blocking mechanism of MICP on lead in soil, investigate the impact of Pb on key genes involved in urease metabolism, enhance the comprehension of the chemical morphology of lead mineralization products, and provide a theoretical foundation for MICP technology in preventing the migration of Pb2+ in soil profiles.

A mesoporous superparamagnetic iron oxide nanoparticle as a generic drug delivery system for tumor ferroptosis therapy.

As a famous drug delivery system (DDS), mesoporous organosilica nanoparticles (MON) are degraded slowly in vivo and the degraded components are not useful for cell nutrition or cancer theranostics, and superparamagnetic iron oxide nanoparticles (SPION) are not mesoporous with low drug loading content (DLC). To overcome the problems of MON and SPION, we developed mesoporous SPIONs (MSPIONs) with an average diameter of 70 nm and pore size of 3.9 nm. Sorafenib (SFN) and/or brequinar (BQR) were loaded into the mesopores of MSPION, generating SFN@MSPION, BQR@MSPION and SFN/BQR@MSPION with high DLC of 11.5% (SFN), 10.1% (BQR) and 10.0% (SNF + BQR), demonstrating that our MSPION is a generic DDS. SFN/BQR@MSPION can be used for high performance ferroptosis therapy of tumors because: (1) the released Fe2+/3+ in tumor microenvironment (TME) can produce •OH via Fenton reaction; (2) the released SFN in TME can inhibit the cystine/glutamate reverse transporter, decrease the intracellular glutathione (GSH) and GSH peroxidase 4 levels, and thus enhance reactive oxygen species and lipid peroxide levels; (3) the released BQR in TME can further enhance the intracellular oxidative stress via dihydroorotate dehydrogenase inhibition. The ferroptosis therapeutic mechanism, efficacy and biosafety of MSPION-based DDS were verified on tumor cells and tumor-bearing mice.

Detection of a Human Adenovirus Outbreak, Including Some Critical Infections, Using Multipathogen Testing at a Large University, September 2022-January 2023.

Background: Human adenoviruses (HAdVs) can cause outbreaks of flu-like illness in university settings. Most infections in healthy young adults are mild; severe illnesses rarely occur. In Fall 2022, an adenovirus outbreak was identified in university students. Methods: HAdV cases were defined as university students 17-26 years old who presented to the University Health Service or nearby emergency department with flu-like symptoms (eg, fever, cough, headache, myalgia, nausea) and had confirmed adenovirus infections by polymerase chain reaction (PCR). Demographic and clinical characteristics were abstracted from electronic medical records; clinical severity was categorized as mild, moderate, severe, or critical. We performed contact investigations among critical cases. A subset of specimens was sequenced to confirm the HAdV type. Results: From 28 September 2022 to 30 January 2023, 90 PCR-confirmed cases were identified (51% female; mean age, 19.6 years). Most cases (88.9%) had mild illness. Seven cases required hospitalization, including 2 critical cases that required intensive care. Contact investigation identified 44 close contacts; 6 (14%) were confirmed HAdV cases and 8 (18%) reported symptoms but never sought care. All typed HAdV-positive specimens (n = 36) were type 4. Conclusions: While most students with confirmed HAdV had mild illness, 7 otherwise healthy students had severe or critical illness. Between the relatively high number of hospitalizations and proportion of close contacts with symptoms who did not seek care, the true number of HAdV cases was likely higher. Our findings illustrate the need to consider a wide range of pathogens, even when other viruses are known to be circulating.

Association of metabolomics with PD-1 inhibitor plus chemotherapy outcomes in patients with advanced non-small-cell lung cancer.

BACKGROUND: Combining immune checkpoint inhibitors (ICIs) with chemotherapy has become a standard treatment for patients with non-small cell lung cancer (NSCLC) lacking driver gene mutations. Reliable biomarkers are essential for predicting treatment outcomes. Emerging evidence from various cancers suggests that early assessment of serum metabolites could serve as valuable biomarkers for predicting outcomes. This study aims to identify metabolites linked to treatment outcomes in patients with advanced NSCLC undergoing first-line or second-line therapy with programmed cell death 1 (PD-1) inhibitors plus chemotherapy. METHOD: 200 patients with advanced NSCLC receiving either first-line or second-line PD-1 inhibitor plus chemotherapy, and 50 patients undergoing first-line chemotherapy were enrolled in this study. The 200 patients receiving combination therapy were divided into a Discovery set (n=50) and a Validation set (n=150). These sets were further categorized into respond and non-respond groups based on progression-free survival PFS criteria (PFS≥12 and PFS<12 months). Serum samples were collected from all patients before treatment initiation for untargeted metabolomics analysis, with the goal of identifying and validating biomarkers that can predict the efficacy of immunotherapy plus chemotherapy. Additionally, the validated metabolites were grouped into high and low categories based on their medians, and their relationship with PFS was analyzed using Cox regression models in patients receiving combination therapy. RESULTS: After the impact of chemotherapy was accounted for, two significant differential metabolites were identified in both the Discovery and Validation sets: N-(3-Indolylacetyl)-L-alanine and methomyl (VIP>1 and p<0.05). Notably, upregulation of both metabolites was observed in the group with a poorer prognosis. In the univariate analysis of PFS, lower levels of N-(3-Indolylacetyl)-L-alanine were associated with longer PFS (HR=0.59, 95% CI, 0.41 to 0.84, p=0.003), and a prolonged PFS was also indicated by lower levels of methomyl (HR=0.67, 95% CI, 0.47 to 0.96, p=0.029). In multivariate analyses of PFS, lower levels of N-(3-Indolylacetyl)-L-alanine were significantly associated with a longer PFS (HR=0.60, 95% CI, 0.37 to 0.98, p=0.041). CONCLUSION: Improved outcomes were associated with lower levels of N-(3-Indolylacetyl)-L-alanine in patients with stage IIIB-IV NSCLC lacking driver gene mutations, who underwent first-line or second-line therapy with PD-1 inhibitors combined with chemotherapy. Further exploration of the potential predictive value of pretreatment detection of N-(3-Indolylacetyl)-L-alanine in peripheral blood for the efficacy of combination therapy is warranted. STATEMENT: The combination of ICIs and chemotherapy has established itself as the new standard of care for first-line or second-line treatment in patients with advanced NSCLC lacking oncogenic driver alterations. Therefore, identifying biomarkers that can predict the efficacy and prognosis of immunotherapy plus chemotherapy is of paramount importance. Currently, the only validated predictive biomarker is programmed cell death ligand-1 (PD-L1), but its predictive value is not absolute. Our study suggests that the detection of N-(3-Indolylacetyl)-L-alanine in patient serum with untargeted metabolomics prior to combined therapy may predict the efficacy of treatment. Compared with detecting PD-L1 expression, the advantage of our biomarker is that it is more convenient, more dynamic, and seems to work synergistically with PD-L1 expression.

Patient-derived tumor-like cell clusters for personalized chemo- and immunotherapies in non-small cell lung cancer.

Many patient-derived tumor models have emerged recently. However, their potential to guide personalized drug selection remains unclear. Here, we report patient-derived tumor-like cell clusters (PTCs) for non-small cell lung cancer (NSCLC), capable of conducting 100-5,000 drug tests within 10 days. We have established 283 PTC models with an 81% success rate. PTCs contain primary tumor epithelium self-assembled with endogenous stromal and immune cells and show a high degree of similarity to the original tumors in phenotypic and genotypic features. Utilizing standardized culture and drug-response assessment protocols, PTC drug-testing assays reveal 89% overall consistency in prospectively predicting clinical outcomes, with 98.1% accuracy distinguishing complete/partial response from progressive disease. Notably, PTCs enable accurate prediction of clinical outcomes for patients undergoing anti-PD1 therapy by combining cell viability and IFN-γ value assessments. These findings suggest that PTCs could serve as a valuable preclinical model for personalized medicine and basic research in NSCLC.

Development and testing of a four-item version of the physical resilience instrument for older adults (PRIFOR-4).

The 16-item Physical Resilience Instrument for Older Adults (PRIFOR) has good clinimetric properties; however, a shortened PRIFOR would greatly enhance physical resilience measurements in clinical settings. The current analysis aimed to reduce the number of PRIFOR while maintaining its clinimetric properties, emphasizing on its factor structure and convergent validity. A longitudinal study was conducted among 863 patients aged 65 years or older. Four PRIFOR items with high factor loadings were selected to generate the short version of PRIFOR (PRIFOR-4). The PRIFOR-4 was found to have a unidimensional structure (comparative fit index = 0.999; Tucker-Lewis index = 0.998 in the confirmatory factor analysis results) with good convergent validity with various external measures (absolute r = 0.109-0.597; p-values<0.01). Because the PRIFOR-4 contains only four items, the completion time for the respondents reduced three fourths from the original PRIFOR, which may have a marked reduction in the response burden. The PRIFOR-4 is thus an easy-to-use measurement that saves time for healthcare professionals in clinical practice.

Importance of AIM2 as a serum marker for reflecting severity and predicting a poor outcome of human severe traumatic brain injury: A prospective longitudinal cohort study.

BACKGROUND: Absent in melanoma 2 (AIM2) participates in neuroinflammation. Here, the prognostic significance of serum AIM2 was explored in severe traumatic brain injury (sTBI). METHODS: A total of 135 sTBI patients and 80 healthy controls were recruited in this prospective cohort study. Serum C-reactive protein (CRP) and AIM2 levels were measured. Glasgow Coma Scale (GCS) and Rotterdam computed tomography (CT) classification were recorded as the severity indicators. Prognostic parameters were posttraumatic six-month extended Glasgow outcome scale (GOSE) scores and poor outcome (GOSE scores of 1-4). RESULTS: As opposed to controls, there were significantly elevated serum AIM2 levels after sTBI. Serum AIM2 levels were independently correlated with serum CRP levels, GCS scores, Rotterdam CT scores, GOSE scores and poor outcome. Also, serum AIM2 levels were efficiently predictive of poor outcome under the receiver operating characteristic (ROC) curve. Under the restricted cubic spline, serum AIM2 levels were linearly correlated with risk of poor outcome. Using subgroup analysis, serum AIM2 levels did not significantly interact with other indices, such as age, gender, alcohol drinking, cigarette smoking, etc. Also, combination model, in which serum AIM2, GCS scores and Rotterdam CT scores were merged, was outlined using nomogram and performed well under calibration curve, ROC curve and decision curve. CONCLUSIONS: Raised serum AIM2 levels after sTBI, in intimate correlation with systemic inflammation and trauma severity, are independently discriminative of posttraumatic six-month neurological outcome, substantializing serum AIM2 as an inflammatory prognostic biomarker of sTBI.

A novel mutation in the ABCC8 gene causing maturity-onset diabetes of the young: A case report.

A 34-year-old woman was diagnosed with type 1 diabetes mellitus and treated with insulin for 24 years. The patient has a family history of diabetes in three consecutive generations. Her Whole exon sequencing showed a heterozygous mutation in the ABCC8 gene, and it also found some of her relatives to carry this mutation. She was diagnosed with MODY12 and received glimepiride therapy with the achievement of good glycaemic control.

Three-Dimensional Self-Supported Ge Anode for Advanced Lithium-Ion Batteries.

Three-dimensional (3D) self-supported Ge anode is one of the promising candidates to replace the traditional graphite anode material for high-performance binder-free lithium-ion batteries (LIBs). The enlarged surface area and the shortened ions/electrons transporting distance of the 3D electrode would greatly facilitate the rapid transfer of abundant lithium ions during cycling, thus achieve enhanced energy and power density during cycling. Cycle stability of the 3D self-supported Ge electrode would be improved due to the obtained enough space could effectively accommodate the large volume expansion of the Ge anode. In this review, we first describe the electrochemical properties and Li ions storage mechanism of Ge anode. Moreover, the recent advances in the 3D self-supported Ge anode architectures design are majorly illustrated and discussed. Challenges and prospects of the 3D self-supported Ge electrode are finally provided, which shed light on ways to design more reliable 3D Ge-based electrodes in energy storage systems.

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection.

Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are among the most prevalent infectious diseases worldwide, with a notable increase in treatment costs due to the emergence of drug-resistant pathogens. Current diagnostic strategies for UTIs, such as urine culture and flow cytometry, require time-consuming protocols and expensive equipment. We present here a machine learning-assisted colorimetric sensor array based on recognition of ligand-functionalized Fe single-atom nanozymes (SANs) for the identification of microorganisms at the order, genus, and species levels. Colorimetric sensor arrays are built from the SAN Fe1-NC functionalized with four types of recognition ligands, generating unique microbial identification fingerprints. By integrating the colorimetric sensor arrays with a trained computational classification model, the platform can identify more than 10 microorganisms in UTI urine samples within 1 h. Diagnostic accuracy of up to 97% was achieved in 60 UTI clinical samples, holding great potential for translation into clinical practice applications.

The role of novel adipokines and adipose-derived extracellular vesicles (ADEVs): Connections and interactions in liver diseases.

Adipose tissues (AT) are an important endocrine organ that secretes various functional adipokines, peptides, non-coding RNAs, and acts on AT themselves or other distant tissues or organs through autocrine, paracrine, or endocrine manners. An accumulating body of evidence has suggested that many adipokines play an important role in liver metabolism. Besides the traditional adipokines such as adiponectin and leptin, many novel adipokines have recently been identified to have regulatory effects on the liver. Additionally, AT can produce extracellular vesicles (EVs) that act on peripheral tissues. However, under pathological conditions, such as obesity and diabetes, dysregulation of adipokines is associated with functional changes in AT, which may cause liver diseases. In this review, we focus on the newly discovered adipokines and EVs secreted by AT and highlight their actions on the liver under the context of obesity, nonalcoholic fatty liver diseases (NAFLD), and some other liver diseases. Clarifying the action of adipokines and adipose tissue-derived EVs on the liver would help to identify novel therapeutic targets or biomarkers for metabolic diseases.