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Abstract Secondary zinc oxide dust is rich in high-grade metals such as Zn, In, Pb, and Ga, and in the face of the depletion of ore resources at home and abroad, it is of great significance to seek an efficient process to realize the full resource recovery of valuable metals in secondary zinc oxide dust. In this study, on the basis of the thermodynamic analysis of the wet treatment process, three wet treatment methods, namely “low acid leaching”, “high acid leaching” and “chlorination leaching”, were used to explore the suitable parameters for stepwise extraction of Zn, In and Pb metals. The results showed that the three wet treatment methods could effectively extract the corresponding main elements, and the optimal leaching rates of Zn, In and Pb were 73, 90 and 94%, respectively. Thermodynamic analysis shows that under ideal conditions, the “cascade separation” of some or all metals can be theoretically achieved by using a suitable leaching solvent for zinc oxide dust. The concentration of sulfuric acid, the ratio of liquid solid volume to mass and temperature had great effects on the leaching rate of Zn and In, and the leaching rate of Zn and In also increased with the increase of the values of the three experimental parameters, which was positively correlated. The leaching rate of Pb will increase with the increase of sulfuric acid concentration, but when the pH of the solution system is

Abstract Background The use of mesenchymal stem cells (MSCs) is recognized as a promising strategy for the treatment of androgenetic alopecia (AGA). However, the underlying mechanism remains to be explored. Here, we evaluated the therapeutic effects and potential mechanisms of the use of human umbilical cord mesenchymal stem cells (hUCMSCs) in dihydrotestosterone (DHT)-induced AGA models in vivo and in vitro. Methods Intradermal transplantation of hUCMSCs was performed in AGA model mice and therapeutic effects were evaluated using histological and immunofluorescence staining. Transwell assays were used for co-culture of hUCMSCs and dermal papilla cells (DPCs), and communication was assessed using RT-qPCR, immunofluorescence, and apoptosis analysis. Interactions between DPCs and hair follicle stem cells (HFSCs) were investigated using RT-qPCR, EdU assays, and cell cycle analysis. Results Treatment of AGA mice with hUCMSCs promoted hair growth, HFs density, skin thickness, and anagen phase activation, while inhibiting DPCs apoptosis, and promoting HFSCs proliferation. In vitro, hUCMSCs activated Wnt/β-catenin signaling in DPCs via Wntless (Wls), while stimulating growth factor secretion and HFSCs proliferation. Blocking β-catenin degradation with MSAB increased DPCs apoptosis, reduced growth factor secretion, and retarded HFSCs proliferation. Conclusion hUCMSCs promoted hair regeneration in AGA model mice. This was found to be dependent on reducing DPCs apoptosis, thereby relieving the inhibitory effects of DPCs on the growth of HFSCs. The activation of the Wnt/β-catenin signaling pathway was shown to play a crucial role in the promotion of hair growth by hUCMSCs in AGA mice.

Abstract Objectives This study aimed to conduct a comprehensive systematic literature review and meta-analysis to assess the risk and outcomes of coronavirus disease 2019 (COVID-19) in patients with rheumatoid arthritis. Methods A systematic search was performed across four electronic databases. The quality of the studies was assessed using the Newcastle‒Ottawa quality assessment scale and the Joanna Briggs Institute critical appraisal checklist. Statistical analyses were conducted using STATA 14 software. Results A total of 62 studies were included in the analysis. First, the meta-analysis revealed the following prevalence rates among rheumatoid arthritis patients: COVID-19, 11%; severe COVID-19, 18%; COVID-19-related hospitalization, 29%; admission to the intensive care unit (ICU) due to COVID-19, 10%; and death from COVID-19, 8%. Second, rheumatoid arthritis was associated with an increased risk of COVID-19 infection (OR 1.045(0.969–1.122), p = 0.006), COVID-19-related hospitalization (OR 1.319(1.055–1.584), p = 0.006), admission to the ICU due to COVID-19 (OR 1.498(1.145–1.850), p = 0.002), and death from COVID-19 (OR 1.377(1.168–1.587), p = 0.001). Third, no statistically significant association was found between rheumatoid arthritis and severe COVID-19 (OR 1.354(1.002–1.706), p = 0.135). Conclusions Rheumatoid arthritis patients have a significantly greater risk of COVID-19 infection, hospitalization, ICU admission, and death than individuals without rheumatoid arthritis. However, rheumatoid arthritis did not show a significant association with the risk of severe COVID-19. These findings underscore the need for tailored management strategies and vigilant monitoring of COVID-19 outcomes in rheumatoid arthritis patients. Systematic Review Registration The study has been registered on PROSPERO [ https://www.crd.york.ac.uk/PROSPERO/ ], and the registration number is CRD42024528119.

Abstract Background and objectives Serum free fatty acids (FFA) are associated with various types of cancer. However, the prognostic value of preoperative serum FFA levels and breast cancer (BC) remains unclear. This study aimed to elucidate the specific relationship between FFA levels and BC outcomes. Methods A retrospective review was conducted on 4133 patients with BC admitted to Sun Yat-sen Memorial Hospital from January 2015 to October 2021. Preoperative serum FFA levels were detected by the enzymatic endpoint method. The relationship between serum FFA levels and clinical characteristics was analyzed based on FFA interquartile range. Restricted cubic splines and multivariate Cox regression analyses were used to assess the relationship between preoperative serum FFA levels and overall survival (OS) in patients with BC. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated. Results According to the FFA interquartile range, FFA levels were significantly correlated with OS (years) (p

Abstract Plant evolution is driven by key innovations of functional traits that enables their survivals in diverse ecological environments. However, plant adaptive evolution from land to atmospheric niches remains poorly understood. In this study, we use the epiphytic Tillandsioideae subfamily of Bromeliaceae as model plants to explore their origin, evolution and diversification. We provide a comprehensive phylogenetic tree based on nuclear transcriptomic sequences, indicating that core tillandsioids originated approximately 11.3 million years ago in the Andes. The geological uplift of the Andes drives the divergence of tillandsioids into tank-forming and atmospheric types. Our genomic and transcriptomic analyses reveal gene variations and losses associated with adaptive traits such as impounding tanks and absorptive trichomes. Furthermore, we uncover specific nitrogen-fixing bacterial communities in the phyllosphere of tillandsioids as potential source of nitrogen acquisition. Collectively, our study provides integrative multi-omics insights into the adaptive evolution of tillandsioids in response to elevated aerial habitats.

Abstract Impaired clearance of amyloid β (Aβ) in late-onset Alzheimer’s disease (AD) affects disease progression. The role of peripheral monocytes in Aβ clearance from the central nervous system (CNS) is unclear. We use a flow cytometry assay to identify Aβ-binding monocytes in blood, validated by confocal microscopy, Western blotting, and mass spectrometry. Flow cytometry immunophenotyping and correlation with AD biomarkers are studied in 150 participants from the AIBL study. We also examine monocytes in human cerebrospinal fluid (CSF) and their migration in an APP/PS1 mouse model. The assay reveals macrophage-like Aβ-binding monocytes with high phagocytic potential in both the periphery and CNS. We find lower surface Aβ levels in mild cognitive impairment (MCI) and AD-dementia patients compared to cognitively unimpaired individuals. Monocyte infiltration from blood to CSF and migration from CNS to peripheral lymph nodes and blood are observed. Here we show that Aβ-binding monocytes may play a role in CNS Aβ clearance, suggesting their potential as a biomarker for AD diagnosis and monitoring.

Abstract Several (inter)national longitudinal dementia observational datasets encompassing demographic information, neuroimaging, biomarkers, neuropsychological evaluations, and muti-omics data, have ushered in a new era of potential for integrating machine learning (ML) into dementia research and clinical practice. ML, with its proficiency in handling multi-modal and high-dimensional data, has emerged as an innovative technique to facilitate early diagnosis, differential diagnosis, and to predict onset and progression of mild cognitive impairment and dementia. In this review, we evaluate current and potential applications of ML, including its history in dementia research, how it compares to traditional statistics, the types of datasets it uses and the general workflow. Moreover, we identify the technical barriers and challenges of ML implementations in clinical practice. Overall, this review provides a comprehensive understanding of ML with non-technical explanations for broader accessibility to biomedical scientists and clinicians.

Abstract The two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae), is a notorious pest in agriculture that has developed resistance to almost all chemical types used for its control. Here, we assembled a chromosome-level genome for the TSSM using Illumina, Nanopore, and Hi-C sequencing technologies. The assembled contigs had a total length of 103.94 Mb with an N50 of 3.46 Mb, with 87.7 Mb of 34 contigs anchored to three chromosomes. The chromosome-level genome assembly had a BUSCO completeness of 94.8%. We identified 15,604 protein-coding genes, with 11,435 genes that could be functionally annotated. The high-quality genome provides invaluable resources for the genetic and evolutionary study of TSSM.

Abstract Hepatocellular carcinomas (HCCs) are characterized by a vast spectrum of somatic copy number alterations (CNAs); however, their functional relevance is largely unknown. By performing a genome‐wide survey on prognosis‐associated focal CNAs in 814 HCC patients by an integrative computational framework based on transcriptomic data, genomic amplification is identified at 8q24.13 as a promising candidate. Further evidence is provided that the 8q24.13 amplification‐driven overexpression of Rab GTPase activating protein TBC1D31 exacerbates HCC growth and metastasis both in vitro and in vivo through activating Epidermal growth factor receptor (EGFR) signaling. Mechanistically, TBC1D31 acts as a Rab GTPase activating protein to catalyze GTP hydrolysis for Rab22A and then reduces the Rab22A‐mediated endolysosomal trafficking and degradation of EGFR. Notably, overexpression of TBC1D31 markedly increases the resistance of HCC cells to lenvatinib, whereas inhibition of the TBC1D31‐EGFR axis can reverse this resistance phenotype. This study highlights that TBC1D31 at 8q24.13 is a new critical oncogene, uncovers a novel mechanism of EGFR activation in HCC, and proposes the potential strategies for treating HCC patients with TBC1D31 amplification or overexpression.

Abstract Developing dynamic color‐tunable ultra‐long room temperature phosphorescence (URTP) polymers with afterglow of over 1 s, photo‐chromism, and multi‐stimuli response for practical anti‐counterfeiting and information security applications is attractive but very challenging. Herein, by doping multicolor phosphorescence pyridinium bromide L block or viologen‐based photo‐chromic V block into polyvinyl alcohol matrixes, the water‐stimuli‐responsive color‐tunable URTP polymer films with afterglow of up to 8 s and the reversible viologen‐based photochromic polymer films have been developed. More significantly, a series of dynamic color‐tunable URTP polymer films with ultra‐long afterglow of over 6 s, photo‐chromism, and water‐stimuli response have been successfully exploited by integrating L and V blocks into one polymer system. Mechanistic investigations have revealed that their photo‐chromism mainly comes from the photo‐generated viologen free radicals. Furthermore, their dynamic multilevel anti‐counterfeiting applications have been demonstrated. These results pave the way to develop smarter multifunctional URTP materials for anti‐counterfeiting and optical sensing.

Summary: Background: It is estimated that ∼60% of people with Alzheimer's disease (AD) are undetected or undiagnosed, with higher rates of underdiagnosis in low-to middle-income areas with limited medical resources. To promote health equity, we have developed a web-based tool that utilizes easy-to-collect clinical data to enhance AD detection rate in primary care settings. Methods: This study was leveraged on the data collected from participants of the Australian Imaging, Biomarker & Lifestyle (AIBL) study and the Religious Orders Study and Memory and Aging Project (ROSMAP). The study included three phases: (1) constructing and evaluating a model on retrospective cohort data (1407 AIBL participants), (2) performing simulated trials to assess model accuracy (30 AIBL participants) and missing data tolerability (30 AIBL participants), and (3) external evaluation using a non-Australian dataset (500 ROSMAP participants). The auto-score machine learning algorithm was employed to develop the Florey Dementia Risk Score (FDRS). All the simulated trials and evaluation were performed using a web-based FDRS tool. Findings: FDRS achieved an area under the curve (AUC) of approximately 0.82 [95% CI, 0.75–0.88], with a sensitivity of 0.74 [0.60–0.86] and a specificity of 0.73 [0.70–0.79]. The accuracy of the simulated pilot trial for 30 AIBL participants with complete record was 87% (26/30 correct), while it only slightly decreased (80.0–83.3%, depending on imputation methods) for another 30 AIBL participants with one or two missing data. FDRS achieved an AUC of 0.82 [0.77–0.86] of 500 ROSMAP participants. Interpretation: The FDRS tool offers a potential low-cost solution to AD screening in primary care. The present study warrants future trials of FDRS for optimization and to confirm its generalizability across a more diverse population, especially people in low-income countries. Funding: National Health and Medical Research Council, Australia (GNT2007912) and Alzheimer's Association, USA (23AARF-1020292).

Abstract Background The associations between mood disorders (anxiety and depression) and mild cognitive impairment (MCI) or Alzheimer’s dementia (AD) remain unclear. Methods Data from the Australian Imaging, Biomarker & Lifestyle (AIBL) study were subjected to logistic regression to determine both cross-sectional and longitudinal associations between anxiety/depression and MCI/AD. Effect modification by selected covariates was analysed using the likelihood ratio test. Results Cross-sectional analysis was performed to explore the association between anxiety/depression and MCI/AD among 2,209 participants with a mean [SD] age of 72.3 [7.4] years, of whom 55.4% were female. After adjusting for confounding variables, we found a significant increase in the odds of AD among participants with two mood disorders (anxiety: OR 1.65 [95% CI 1.04–2.60]; depression: OR 1.73 [1.12–2.69]). Longitudinal analysis was conducted to explore the target associations among 1,379 participants with a mean age of 71.2 [6.6] years, of whom 56.3% were female. During a mean follow-up of 5.0 [4.2] years, 163 participants who developed MCI/AD (refer to as PRO) were identified. Only anxiety was associated with higher odds of PRO after adjusting for covariates (OR 1.56 [1.03–2.39]). However, after additional adjustment for depression, the association became insignificant. Additionally, age, sex, and marital status were identified as effect modifiers for the target associations. Conclusion Our study provides supportive evidence that anxiety and depression impact on the evolution of MCI/AD, which provides valuable epidemiological insights that can inform clinical practice, guiding clinicians in offering targeted dementia prevention and surveillance programs to the at-risk populations.

Abstract C − N axially chiral compounds have recently attracted significant interest among synthetic chemistry community due to their widespread application in pharmaceuticals, advanced materials and organic synthesis. Although the emerging asymmetric Catellani reaction offers great opportunity for their modular and efficient preparation, the only operative chiral NBE strategy to date requires using half stoichiometric amount of chiral NBE and 2,6-disubstituted bromoarenes as electrophiles. We herein report an efficient assembly of C–N axially chiral scaffolds through a distinct chiral ligand strategy. The crucial chiral source, a biimidazoline (BiIM) chiral dinitrogen ligand, is used in relatively low loading and permits the use of less bulky bromoarenes. The method also features the use of feedstock plain NBE, high reactivity, good enantioselectivity, ease of operation and scale-up. Applications in the preparation of chiral optoelectronic material candidates featuring two C–N chiral axes and a chiral ligand for asymmetric C–H activation have also been demonstrated.

Highlights The homogeneous hybridization of organic–inorganic-metal elements in 3D aerogel was achieved by an expeditious method. The aerogel tightly integrates excellent thermal insulation (49.6 mW m−1 K−1), ablative resistance, mechanical strength, and superhydrophobic properties. The ablated carbon aerogel combines notable electromagnetic interference shielding properties (31.6 dB) and load-carrying properties (272.8 kN·m kg−1).

Abstract Objectives To noninvasively detect prostate cancer and predict the Gleason grade using single-modality T2-weighted imaging with a deep-learning approach. Methods Patients with prostate cancer, confirmed by histopathology, who underwent magnetic resonance imaging examinations at our hospital during September 2015–June 2022 were retrospectively included in an internal dataset. An external dataset from another medical center and a public challenge dataset were used for external validation. A deep-learning approach was designed for prostate cancer detection and Gleason grade prediction. The area under the curve (AUC) was calculated to compare the model performance. Results For prostate cancer detection, the internal datasets comprised data from 195 healthy individuals (age: 57.27 ± 14.45 years) and 302 patients (age: 72.20 ± 8.34 years) diagnosed with prostate cancer. The AUC of our model for prostate cancer detection in the validation set (n = 96, 19.7%) was 0.918. For Gleason grade prediction, datasets comprising data from 283 of 302 patients with prostate cancer were used, with 227 (age: 72.06 ± 7.98 years) and 56 (age: 72.78 ± 9.49 years) patients being used for training and testing, respectively. The external and public challenge datasets comprised data from 48 (age: 72.19 ± 7.81 years) and 91 patients (unavailable information on age), respectively. The AUC of our model for Gleason grade prediction in the training set (n = 227) was 0.902, whereas those of the validation (n = 56), external validation (n = 48), and public challenge validation sets (n = 91) were 0.854, 0.776, and 0.838, respectively. Conclusion Through multicenter dataset validation, our proposed deep-learning method could detect prostate cancer and predict the Gleason grade better than human experts. Critical relevance statement Precise prostate cancer detection and Gleason grade prediction have great significance for clinical treatment and decision making. Key Points Prostate segmentation is easier to annotate than prostate cancer lesions for radiologists. Our deep-learning method detected prostate cancer and predicted the Gleason grade, outperforming human experts. Non-invasive Gleason grade prediction can reduce the number of unnecessary biopsies. Graphical Abstract

Abstract The structure and mechanism of the human visual system contain rich treasures, and surprising effects can be achieved by simulating the human visual system. In this article, starting from the human visual system, we compare and discuss the discrepancies between the human visual system and traditional machine vision systems. Given the wide variety and large volume of visual information, the use of non-von Neumann structured, flexible neuromorphic vision sensors can effectively compensate for the limitations of traditional machine vision systems based on the von Neumann architecture. Firstly, this article addresses the emulation of retinal functionality and provides an overview of the principles and circuit implementation methods of non-von Neumann computing architectures. Secondly, in terms of mimicking the retinal surface structure, this article introduces the fabrication approach for flexible sensor arrays. Finally, this article analyzes the challenges currently faced by non-von Neumann flexible neuromorphic vision sensors and offers a perspective on their future development.

Straw mulching is a widespread practice for reducing the soil carbon loss caused by erosion. However, the effects of straw mulching on dissolved organic matter (DOM) runoff loss from black soil are not well studied. How straw mulching affects the composition and loss of runoff DOM by changing soil aggregates remains largely unclear. Here, a straw mulching treatment was compared to a no mulching treatment (as a control) on sloping farmland with black soil erosion in Northeast China. We divided the soil into large macroaggregates (>2 mm), small macroaggregates (0.25–2 mm), and microaggregates (

Insecticides play a crucial role in safeguarding crops from pest. However, prior to their release, it is essential to assess the efficacy and potential effects of these protectants. Flupyradifurone (FBF) and sulfoxaflor (SFX), two insecticides commonly used to control aphids, have been found to exert negative effects on the growth and development of Binodoxys communis Gahan, a beneficial parasitic wasp that targets aphids. However, it remains unknown if FBF and SFX influence the symbiotic bacteria residing within B. communis. In this study, 16SrRNA sequencing was utilized to assess the populations of B. communis symbionts exposed to sublethal concentrations (LC10 and LC25) of FBF and SFX. The control and treatment groups exhibited similar bacterial community structures, with Bacteroidota identified as the dominant phylum in each. After exposure to FBF and SFX, the diversity and richness of symbionts (Firmicutes, Bacteroidota, and Actinobacteriota) in B. communis changed notably. The two different insecticides and exposure durations exerted distinct effects on the microbial community. For instance, SFX stress resulted in a decrease in Akkermansia and an increase in Escherichia Shigella 1h after exposure, with both returning to baseline levels after 3d. In contrast, FBF exposure caused a reduction in Akkermansia presence after 1h, which persisted even after 3d. This study represents the first assessment of the effects of FBF and SFX exposure on symbiotic bacteria in B. communis, expanding our understanding of how insecticides influence natural enemies and their symbiotic bacterial relationships. This study provides theoretical guidance for field applications of FBF and SFX, as well as a reasonable basis for exploring chemical resistance conferred by symbiotic bacteria.

BackgroundPostoperative Intestinal Adhesions (PIAs) remain a significant complication of abdominal surgery that can cause pain, infertility, and a potentially lethal bowel obstruction. Kangnian (KN) decoction, a Traditional Chinese Medicine prescription, has been shown to be effective in treating PIAs. Nevertheless, its underlying mechanisms remain unclear.ObjectiveThis study aims to explore the therapeutic effects of KN decoction in a PIA rat model, as well as its potential mechanisms via metabolomics and proteomics analyses.Materials and methods60 rats were randomly assigned to six groups: Normal Control (NC), PIA model, Dexamethasone, KN-Low, KN-Medium, and KN-High. The PIA model was created by abdominal surgery under anesthesia. Pathological damage was evaluated through H&E staining and adhesion grading of affected tissues. The levels of serum cytokines (IL-1β, IL-6, TNF-α, and TGF-1), Connective Tissue Growth Factor (CTGF), and Motilin (MTL) in adherent intestinal tissues were detected using ELISA kits. Untargeted metabolomics was used to investigate potential metabolic pathways of the KN decoction intervention in intestinal adhesions and to screen for differential biomarkers. The label-free quantitative proteomics technique was employed to detect Differentially Expressed Proteins and for biological function and pathway enrichment analyses.ResultsIn PIA rats, KN decoction significantly improved the pathological injury associated with intestinal adhesions and effectively regulated the blood inflammation indicators. Furthermore, KN presented a favorable anti-fibrotic and protective effect against abdominal adhesions, effectively modifying gastrointestinal motility disorders in PIA rats. We identified 58 variables as potential biomarkers and discovered seven main pathological pathways that may be associated with PIAs. Proteomics analysis revealed 75 DEPs that were primarily involved in Valine, leucine, and isoleucine degradation, the MAPK signaling pathway, and retrograde endocannabinoid signaling.ConclusionThis study proved that KN reduces intestinal mucosal injury, downregulates inflammatory factors, and alleviates intestinal adhesions, thus protecting the intestinal barrier function in PIA rats. The combination of proteomics and metabolomics provided a feasible approach for unraveling the therapeutic mechanism of KN decoction in PIAs.

Background: Neurodevelopmental disorder with spasticity, cataracts, and cerebellar hypoplasia (NEDSCAC), induced by MED27 gene, is an autosomal recessive rare disorder characterized by widespread developmental delay with varying degrees of intellectual impairment. Other symptoms include limb spasticity, cataracts, and cerebellar hypoplasia. So far there have been limited reports on NEDSCAC. Methods: In this study, we conducted genetic testing on a child presenting with developmental delay as the primary clinical feature. The genetic test results indicated the presence of novel homozygous missense variants c.74G > A, p.(Arg25His) in the MED27 gene. In vitro functional validation experiments, including plasmid construction and cell transfection, Western blotting, and molecular dynamics structural modeling, were performed on the MED27 Arg25His variant. Results: The results demonstrated a significant reduction in protein expression of MED27 Arg25His and indicated may weaken the interaction force between the MED27 subunit and MED14 subunit. Conclusions: This study expands our understanding of MED27 gene variants and their associated clinical phenotypes. Additionally, it contributes to the investigation of the potential pathogenesis of NEDSCAC caused by MED27 gene variants.

IntroductionPharmacological management is a vital aspect of dementia care. Suboptimal medication prescribing and adverse drug reactions are major causes for ongoing concerns for the quality of care. This review aims to investigate the existence and comprehensiveness of Australian guidelines dedicated to supporting dementia care in the context of pharmacological management.MethodsGuideline registries and databases (EMBASE and CINAHL) were searched to identify Australian guidelines addressing pharmacological management in dementia care and to uncover barriers and considerations associated with guideline implementation.ResultsSeven Australian guidelines were identified. Barriers to effective implementation were identified at individual, provider, and system levels. None of the identified guidelines provided comprehensive guidance on management of multimorbidity and polypharmacy.DiscussionAlthough Australian guidelines are available to guide pharmacological management in dementia, several barriers impede their effective implementation. There is an urgent need for updated guidelines that address the management of multimorbidity and polypharmacy in people living with dementia.