Host selection by thrips is affected by the floral volatile profile of sunflower.

Thrips, Frankliniella intonsa, is a highly polyphagous pest with a worldwide distribution. F. intonsa-infested sunflower seeds show marked visual damage. The study findings revealed that significantly more F. intonsa infested confection sunflower compared to oilseed sunflower, via olfactometer bioassay studies, we found that compared with the flower and pollen of oilseed sunflowers, those of confection sunflowers attract F. intonsa. Considering this discrepancy in the preference of F. intonsa on oilseed and confection sunflowers, the volatiles of the flower and pollens of two sunflowers were analysed by gas chromatography-mass spectroscopy. The behavioural responses of F. intonsa were assessed for these compounds using Y-tube bioassays. Geranyl bromide, a unique volatile component of oilseed sunflowers, induced an assertive approach-avoidance behaviour in F. intonsa, whereas the unique component ethyl isovalerate in confection sunflowers attracted F. intonsa. F. intonsa adults demonstrated significant attraction to the blends of confection sunflowers. Furthermore, field verification revealed that intercropping confection and oilseed sunflowers could effectively control F. intonsa. The study provided insights into the chemical cues used by F. intonsa in locating hosts. Therefore, oilseed sunflowers can be used as repellent plants to prevent F. intonsa invasion.

Covalent Organic Frameworks for Electrocatalysis：Design, Applications, and Perspectives.

Covalent organic frameworks (COFs) are an innovative class of crystalline porous polymers composed of light elements such as C, N, O, etc., linked by covalent bonds. The distinctive properties of COFs, including designable building blocks, large specific surface area, tunable pore size, abundant active sites, and remarkable stability, have led their widespread applications in electrocatalysis. In recent years, COF-based electrocatalysts have made remarkable progress in various electrocatalytic fields, including the hydrogen evolution reaction, oxygen evolution reaction, oxygen reduction reaction, nitrogen reduction reaction, nitrate reduction reaction, and carbon dioxide reduction reaction. This review begins with an introduction to the design and synthesis strategies employed for COF-based electrocatalysts. These strategies include heteroatom doping, metalation of COF and building monomers, encapsulation of active sites within COF pores, and the development of COF-based derived materials. Subsequently, a systematic overview of the recent advancements in the application of COF-based catalysts in electrocatalysis is presented. Finally, the review discusses the main challenges and outlines possible avenues for the future development of COF-based electrocatalysts.

Commercial Chinese polyherbal preparation Zao Ren An Shen prescription for primary insomnia: a systematic review with meta-analysis and trial sequential analysis.

Background: Natural products are widely used for primary insomnia (PI). This systematic review with trial sequential analysis (TSA) aimed to summarize evidence pertaining to the effectiveness and safety of Zao Ren An Shen (ZRAS) prescription, a commercial Chinese polyherbal preparation, for treating PI. Methods: Controlled clinical trials appraising ZRAS compared to controls or as an add-on treatment were systematically searched across seven databases until January 2024. Cochrane ROB 2.0 and ROBINS-I tools were adopted to determine risk of bias. Quality of evidence was assessed using the GRADE framework. Results: We analyzed 22 studies, involving 2,142 participants. The effect of ZRAS in reducing Pittsburgh Sleep Quality Index scores was found to be comparable to benzodiazepines [MD = 0.39, 95%CI (-0.12, 0.91), p = 0.13] and superior to Z-drugs [MD = -1.31, 95%CI (-2.37, -0.24), p = 0.02]. The addition of ZRAS to hypnotics more significantly reduced polysomnographically-recorded sleep onset latency [MD = -4.44 min, 95%CI (-7.98, -0.91), p = 0.01] and number of awakenings [MD = -0.89 times, 95%CI (-1.67, -0.10), p = 0.03], and increased total sleep time [MD = 40.72 min, 95%CI (25.14, 56.30), p < 0.01], with fewer adverse events than hypnotics alone. TSA validated the robustness of these quantitative synthesis results. However, the quality of evidence ranged from very low to low. The limited data available for follow-up did not support meta-synthesis. Conclusion: While ZRAS prescription shows promising effectiveness in treating PI, the overall quality of evidence is limited. Rigorously-designed randomized control trials are warranted to confirm the short-term efficacy of ZRAS and explore its medium-to-long-term efficacy. Systematic Review Registration: (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=471497), identifier (CRD42023471497).

Leveraging AI techniques for predicting spatial distribution and determinants of carbon emission in China's Yangtze River Delta.

This study focuses on the prediction and management of carbon emissions (CE) under the backdrop of global warming, with a particular emphasis on developing spatial planning strategies for urban clusters. In this context, we integrate artificial intelligence technologies to devise an optimized spatial analysis method based on the attributes of multi-source, urban-level spatio-temporal big data on CE. This method enhances both the accuracy and interpretability of CE data processing. Our objectives are to accurately analyze the current status of CE, predict the future spatial distribution of urban CE in the Yangtze River Delta (YRD), and identify key driving factors. We aim to provide pragmatic recommendations for sustainable urban carbon management planning. The findings indicate that: (1) the algorithm designed by us demonstrates excellent fitting capabilities in the analysis of CE data in the YRD, achieving a fitting accuracy of 0.93; (2) it is predicted that from 2025 to 2030, areas with higher CE in the YRD will be primarily concentrated in the 'Provincial Capital Belt' and the 'Heavy Industry Belt'; (3) the economic foundation has been identified as the most significant factor influencing CE in the YRD; (4) projections suggest that CE in the YRD are likely to peak by 2030.

Voltage-dependent anion channel 1 mediates mitochondrial fission and glucose metabolic reprogramming in response to ionizing radiation.

The ionizing radiation (IR) represents a formidable challenge as an environmental factor to mitochondria, leading to disrupt cellular energy metabolism and posing health risks. Although the deleterious impacts of IR on mitochondrial function are recognized, the specific molecular targets remain incompletely elucidated. In this study, HeLa cells subjected to γ-rays exhibited concomitant oxidative stress, mitochondrial structural alterations, and diminished ATP production capacity. The γ-rays induced a dose-dependent induction of mitochondrial fission, simultaneously manifested by an elevated S616/S637 phosphorylation ratio of the dynamin-related protein 1 (DRP1) and a reduction in the expression of the mitochondrial fusion protein mitofusin 2 (MFN2). Knockdown of DRP1 effectively mitigated γ-rays-induced mitochondrial network damage, implying that DRP1 phosphorylation may act as an effector of radiation-induced mitochondrial damage. The mitochondrial outer membrane protein voltage-dependent anion channel 1 (VDAC1) was identified as a crucial player in IR-induced mitochondrial damage. The VDAC1 inhibitor 4,4'-diisothiocyanatostilbene-2,2'-disulfonic acid (DIDS), counteracts the excessive mitochondrial fission induced by γ-rays, consequently rebalancing the glycolytic and oxidative phosphorylation equilibrium. This metabolic shift was uncovered to enhance glycolytic capacity, thus fortifying cellular resilience and elevating the radiosensitivity of cancer cells. These findings elucidate the intricate regulatory mechanisms governing mitochondrial morphology under radiation response. It is anticipated that the development of targeted drugs directed against VDAC1 may hold promise in augmenting the sensitivity of tumor cells to radiotherapy and chemotherapy.

Characteristics of deformation and damage of surrounding rock along the top roadway in the working face of an isolated island and its evolution law.

This study investigates the deformation and damage characteristics of the surrounding rock along the top return mining roadway of an isolated island working face at different stages and reveals its damage mechanism and evolution law. Utilizing a mine in Yangquan City, Shanxi Province, China, as the engineering background, this research employs FLAC 3D numerical simulation and on-site measurements. The findings suggest that the evolution of the plastic zone along the top roadway of the 15,106 island face is largely similar during both the excavation and mining periods. The plastic zones on either side of the roadway are expanding asymmetrically and gradually merging into the plastic zone of the coal pillar. In the destructive stage, the sub-gangs of the roadway are penetrated, indicating the progression into the plastic zone. The investigation points to extensive damage on the larger side of the roadway, the development of fissures, and the significant depth of damage as primary causes of roadway deformation. Moreover, the extent of the plastic zones on both sides of the roadway correlates positively with their relative distance. Continuous monitoring reveals an ongoing increase in roadway displacement, consistent with general observations in coal mining. The results provide valuable insights for optimizing support structures in similar mining environments.

AI models predicting breast cancer distant metastasis using LightGBM with clinical blood markers and ultrasound maximum diameter.

Breast cancer metastasis significantly impacts women's health globally. This study aimed to construct predictive models using clinical blood markers and ultrasound data to predict distant metastasis in breast cancer patients, ensuring clinical applicability, cost-effectiveness, relative non-invasiveness, and accessibility of these models. Analysis was conducted on data from 416 patients across two centers, focusing on clinical blood markers (tumor markers, liver and kidney function indicators, blood lipid markers, cardiovascular biomarkers) and maximum lesion diameter from ultrasound. Feature reduction was performed using Spearman correlation and LASSO regression. Two models were built using LightGBM: a clinical model (using clinical blood markers) and a combined model (incorporating clinical blood markers and ultrasound features), validated in training, internal test, and external validation (test1) cohorts. Feature importance analysis was conducted for both models, followed by univariate and multivariate regression analyses of these features. The AUC values of the clinical model in the training, internal test, and external validation (test1) cohorts were 0.950, 0.795, and 0.883, respectively. The combined model showed AUC values of 0.955, 0.835, and 0.918 in the training, internal test, and external validation (test1) cohorts, respectively. Clinical utility curve analysis indicated the combined model's superior net benefit in identifying breast cancer with distant metastasis across all cohorts. This suggests the combined model's superior discriminatory ability and strong generalization performance. Creatine kinase isoenzyme (CK-MB), CEA, CA153, albumin, creatine kinase, and maximum lesion diameter from ultrasound played significant roles in model prediction. CA153, CK-MB, lipoprotein (a), and maximum lesion diameter from ultrasound positively correlated with breast cancer distant metastasis, while indirect bilirubin and magnesium ions showed negative correlations. This study successfully utilized clinical blood markers and ultrasound data to develop AI models for predicting distant metastasis in breast cancer. The combined model, incorporating clinical blood markers and ultrasound features, exhibited higher accuracy, suggesting its potential clinical utility in predicting and identifying breast cancer distant metastasis. These findings highlight the potential prospects of developing cost-effective and accessible predictive tools in clinical oncology.

Application of whole exome sequencing in carrier screening for high-risk families without probands.

Purpose: This study aimed to screen the genetic etiology for the high-risk families including those with an adverse pregnancy history, a history of consanguineous marriages, or a history of genetic diseases, but lack of proband via whole exome sequencing (WES). Methods: 128 individuals from high-risk family were tested by WES. The candidate variants were analyzed according to the ACMG criteria to screen the potential carriers. At-risk couples (ARCs) who harbored the same causative gene were provided with precise fertility guidance to avoid the birth of children with birth defects. Results: The total detection rate was 36.72%, with pathogenic/likely pathogenic (P/LP) variants found in 47 individuals, and variants of uncertain significance (VUS) were found in 34. Among couples with adverse pregnancy history: P/LP variants were found in 38 individuals, and VUS were found in 26, for a detection rate of 34.55%; among members of family history of genetic disease or consanguineous marriages: P/LP variants were found in nine individuals, and VUS were found in 8, for a detection rate of 50.00%. Otherwise, we detected 19 ARCs who both carried P/LP variants in the same gene, with a theoretical offspring prevalence of up to 7.42%. Conclusion: In the absence of probands, carrier screening using WES can provide an efficient tool for screening the molecular etiology of high-risk families.

Cell-recruited microspheres for OA treatment by dual-modulating inflammatory and chondrocyte metabolism.

Osteoarthritis (OA) is a degenerative disease potentially exacerbated due to inflammation, cartilage degeneration, and increased friction. Both mesenchymal stem cells (MSCs) and pro-inflammatory macrophages play important roles in OA. A promising approach to treating OA is to modify multi-functional hydrogel microspheres to target the OA microenvironment and structure. Arginyl-glycyl-aspartic acid (RGD) is a peptide widely used in bioengineering owing to its cell adhesion properties, which can recruit BMSCs and macrophages. We developed TLC-R, a microsphere loaded with TGF-ß1-containing liposomes. The recruitment effect of TLC-R on macrophages and BMSCs was verified by in vitro experiments, along with its function of promoting chondrogenic differentiation of BMSCs. And we evaluated the effect of TLC-R in balancing OA metabolism in vitro and in vivo. When TLC-R was co-cultured with BMSCs and lipopolysaccharide (LPS)-treated macrophages, it showed the ability to recruit both cells in substantial numbers. As the microspheres degraded, TGF-ß1 and chondroitin sulfate (ChS) were released to promote chondrogenic differentiation of the recruited BMSCs, modulate chondrocyte metabolism and inhibit inflammation induced by the macrophages. Furthermore, in vivo analysis showed that TLC-R restored the narrowed space, reduced osteophyte volume, and improved cartilage metabolic homeostasis in OA rats. Altogether, TLC-R provides a comprehensive and novel solution for OA treatment by dual-modulating inflammatory and chondrocyte metabolism.

STAT5B Suppresses Ferroptosis by Promoting DCAF13 Transcription to Regulate p53/xCT Pathway to Promote Mantle Cell Lymphoma Progression.

Objective: The purpose of this study was to analyze the mechanism by which STAT5B inhibits ferroptosis in mantle cell lymphoma (MCL) by promoting DCAF13 transcriptional regulation of p53/xCT pathway. Methods: The correlations between STAT5B, DCAF13 and ferroptosis in MCL were analyzed using Gene Expression Profiling Interactive Analysis (GEPIA, http://gepia.cancer-pku.cn/index.html). The expression levels and pairwise correlations of STAT5B, DCAF13, p53 and xCT in MCL patients were detected, respectively. STAT5B was silenced to confirm their criticality in MCL ferroptosis. the effects of blocking necrosis, apoptosis and ferroptosis on the anti-MCL effects of STAT5B were examined. Cells with STAT5B overexpression and/or DCAF13 silencing were constructed to confirm the involvement of DCAF13 in the STAT5B-regulated p53/xCT pathway. The regulation of p53 ubiquitination was confirmed by DCAF13 overexpression and MG132. The effects of silencing DCAF13 and MG132 on STAT5B overexpression on MCL was clarified by a tumor-bearing nude mouse model. Results: DCAF13 was overexpressed in MCL and positively correlated with STAT5B, negatively correlated with p53, and positively correlated with xCT. Inhibition of ferroptosis alleviated the inhibitory effects of siSTAT5B on MCL, while inhibition of necrosis and apoptosis had few effects. Silencing of DCAF13 led to the blocking of STAT5B regulation of p53/xCT and ferroptosis. The changes in DCAF13 and the addition of MG132 did not have statistically significant effects on p53 mRNA. Elevation of DCAF13 resulted in downregulation of p53 protein levels, and this inhibition was reversed by MG132. In animal models, the promotion of MCL and the inhibition of ferroptosis by STAT5B. Silencing of DCAF13 blocked STAT5B inhibition of p53 and induction of xCT, GPX4, and GSH. Conclusion: STAT5B suppresses ferroptosis by promoting DCAF13 transcription to regulate p53/xCT pathway to promote MCL progression.

Highly dispersed noble metal nanoparticle composites on biomass-derived carbon-based carriers: synthesis, characterization, and catalytic applications.

Precious metal nanoparticles have been widely investigated due to their excellent activity shown in catalysis and sensing. However, how to prepare highly dispersed noble metal nanoparticles to improve the lifetime of catalysts and reduce the cost is still an urgent problem to be solved. In this study, a carbon-based carrier material was prepared by an expansion method and loaded with Pd or Ag nanoparticles on this carbon material to synthesize precious metal nanoparticle composites, which were characterized in detail. The results show that the nanoparticles prepared using this method exhibit superior dispersion. Under the synergistic effect of noble metal nanoparticles and porous carbon carriers, the composites exhibited excellent catalytic degradation of p-nitrophenol and showed excellent sensing performance in the modified hydrogen peroxide sensor electrode. This approach is highly informative for the preparation of nanocomposites in medical and environmental fields.

Computed tomography radiomics study of invasion and instability of lung adenocarcinoma manifesting as ground glass nodule.

Background: Ground-glass nodule (GGN) is the most common manifestation of lung adenocarcinoma on computed tomography (CT). Clinically, the success rate of preoperative diagnosis of GGN by puncture biopsy and other means is still low. The aim of this study is to investigate the clinical and radiomics characteristics of lung adenocarcinoma presenting as GGN on CT images using radiomics analysis methods, establish a radiomics model, and predict the classification of pathological tissue and instability of GGN type lung adenocarcinoma. Methods: This study retrospectively collected 249 patients with 298 GGN lesions who were pathologically confirmed of having lung adenocarcinoma. The images were imported into the Siemens scientific research prototype software to outline the region of interest and extract the radiomics features. Logistic model A (a radiomics model to identify the infiltration of lung adenocarcinoma manifesting as GGNs) was established using features after the dimensionality reduction process. The receiver operating characteristic (ROC) curve of the model on training set and the verification set was drawn, and the area under the curve (AUC) was calculated. Second, a total of 112 lesions were selected from 298 lesions originating from CT images of at least two occasions, and the time between the first CT and the preoperative CT was defined as not less than 90 days. The mass doubling time (MDT) of all lesions was calculated. According to the different MDT diagnostic thresholds instability was predicted. Finally, their AUCs were calculated and compared. Results: There were statistically significant differences in age and lesion location distribution between the "noninvasive" lesion group and the invasive lesion group (P<0.05), but there were no statistically significant differences in sex (P>0.05). Model A had an AUC of 0.89, sensitivity of 0.75, and specificity of 0.86 in the training set and an AUC of 0.87, sensitivity of 0.63, and specificity of 0.90 in the validation set. There was no significant difference statistically in MDT between "noninvasive" lesions and invasive lesions (P>0.05). The AUCs of radiomics models B1, B2 and B3 were 0.89, 0.80, and 0.81, respectively; the sensitivities were 0.71, 0.54, and 0.76, respectively; the specificities were 0.83, 0.77, and 0.60, respectively; and the accuracies were 0.78, 0.65, and 0.69, respectively. Conclusions: There were statistically significant differences in age and location of lesions between the "noninvasive" lesion group and the invasive lesion group. The radiomics model can predict the invasiveness of lung adenocarcinoma manifesting as GGNs. There was no significant difference in MDT between "noninvasive" lesions and invasive lesions. The radiomics model can predict the instability of lung adenocarcinoma manifesting as GGN. When the threshold of MDT was set at 813 days, the model had higher specificity, accuracy, and diagnostic efficiency.

PBMC-mediated modulation of macrophage polarization in RAW264.7 cells through STAT1/STAT6 signaling cascades.

Peripheral blood mononuclear cells (PBMC), sourced autologously, offer numerous advantages when procured: easier acquisition process, no in vitro amplification needed, decreased intervention and overall increased acceptability make PBMC an attractive candidate for cell therapy treatment. However, the exact mechanism by which PBMC treat diseases remains poorly understood. Immune imbalance is the pathological basis of many diseases, with macrophages playing a crucial role in this process. However, research on the role and mechanisms of PBMC in regulating macrophages remains scarce. This study employed an in vitro co-culture model of PBMC and RAW264.7 macrophages to explore the role and mechanisms of PBMC in regulating macrophages. The results showed that the co-culturing led to decreased expression of inflammatory cytokines and increased expression of anti-inflammatory cytokines in RAW264.7 or in the culture supernatant. Additionally, the pro-inflammatory, tissue matrix-degrading M1 macrophages decreased, while the anti-inflammatory, matrix-synthesizing, regenerative M2 macrophages increased in both RAW264.7 and monocytes within PBMC. Moreover, co-cultured macrophages exhibited a significantly decreased p-STAT1/STAT1 ratio, while the p-STAT6/STAT6 ratio significantly increased. This suggests that PBMC may inhibit M1 macrophage polarization by blocking STAT1 signaling cascades and may promote M2 macrophage polarization through the activation of STAT6 signaling cascades. Overall, this study sheds light on the role and mechanism of PBMC in regulating macrophages. Moreover, it was found that monocytes within co-cultured PBMC differentiated into M2 macrophages in the presence of macrophages. This finding provides experimental evidence for the use of PBMC in treating inflammatory diseases, especially macrophage-depleting inflammatory diseases such as osteoarthritis.

Three-dimensional high-aspect-ratio microarray thick electrodes for high-rate hybrid supercapacitors.

Hybrid supercapacitors (HSCs) with facile integration and high process compatibility are considered ideal power sources for portable consumer electronics. However, as a crucial component for storing energy, traditional thin-film electrodes exhibit low energy density. Although increasing the thickness of thin films can enhance the energy density of the electrodes, it gives rise to issues such as poor mechanical stability and long electron/ion transport pathways. Constructing a stable three-dimensional (3D) ordered thick electrode is considered the key to addressing the aforementioned contradictions. In this work, a manufacturing process combining lithography and chemical deposition techniques is developed to produce large-area and high-aspect-ratio 3D nickel ordered cylindrical array (NiOCA) current collectors. Positive electrodes loaded with nickel-cobalt bimetallic hydroxide (NiOCA/NiCo-LDH) are constructed by electrodeposition, and HSCs are assembled with NiOCA/nitrogen-doped porous carbon (NiOCA/NPC) as negative electrodes. The HSCs exhibits 55% capacity retention with the current density ranging from 2 to 50 mA cm-2. Moreover, it maintains 98.2% of the initial capacity after long-term cycling of 15,000 cycles at a current density of 10 mA cm-2. The manufacturing process demonstrates customizability and favorable repeatability. It is anticipated to provide innovative concepts for the large-scale production of 3D microarray thick electrodes for high-performance energy storage system.

Application of cell transplantation in the treatment of neuropathic pain.

Nerve injury can not only lead to sensory and motor dysfunction, but also be complicated with neuropathic pain (NPP), which brings great psychosomatic injury to patients. At present, there is no effective treatment for NPP. Based on the functional characteristics of cell transplantation in nerve regeneration and injury repair, cell therapy has been used in the exploratory treatment of NPP and has become a promising treatment of NPP. In this article, we discuss the current mainstream cell types for the treatment of NPP, including Schwann cells, olfactory ensheathing cells, neural stem cells and mesenchymal stem cells in the treatment of NPP. These bioactive cells transplanted into the host have pharmacological properties of decreasing pain threshold and relieving NPP by exerting nutritional support, neuroprotection, immune regulation, promoting axonal regeneration, and remyelination. Cell transplantation can also change the microenvironment around the nerve injury, which is conducive to the survival of neurons. It can effectively relieve pain by repairing the injured nerve and rebuilding the nerve function. At present, some preclinical and clinical studies have shown that some encouraging results have been achieved in NPP treatment based on cell transplantation. Therefore, we discussed the feasible strategy of cell transplantation as a treatment of NPP and the problems and challenges that need to be solved in the current application of cell transplantation in NPP therapy.

Association between thyroid function and nonalcoholic fatty liver disease: a dose-response meta-analysis.

Background: Thyroid hormones (THs) have been found that it is closely associated with the onset and progression of non-alcoholic fatty liver disease (NAFLD). However, the current study could not verify the intrinsic relationship between thyroid hormones and NAFLD, which requires further research. Methods: The searches of studies reported both TH level in serum and NAFLD were performed in PubMed, Web of Science, Cochrane Library, and Embase databases. We combined an overall meta-analysis with a dose-response meta-analysis to assess the correlation and dose-response relationship between thyroid function levels and the risk of NAFLD. Results: Overall, 10 studies were included with a total of 38,425 individuals. We found that the non-linear dose-response model showed that for every 1 ng/dL increase in FT4, the risk of NAFLD was reduced by 10.56% (p=0.003). The odds ratios (ORs) for NAFLD with high free triiodothyronine (FT3) exposure compared to those with low FT3 were 1.580 (95% CI 1.370 to 1.830, I2 = 0.0%, p<0.001) in the overall meta-analysis. The continuous variable meta-analysis indicated that individuals with high levels of TSH (SMD=1.32, 95% CI 0.660 to 1.970, p<0.001) had significantly higher levels of liver fibrosis than those with low levels. Conclusions: Our findings only validate that there is a correlation between the occurrence of NAFLD and abnormal levels of THs, and it is expected that more observational studies will still be conducted in the future to further demonstrate the relationship between thyroid hormones and NAFLD. Trial registration: Registered number in PROSPERO: CRD42023405052.

Organoid co-culture models of the tumor microenvironment promote precision medicine.

In recent years, the three-dimensional (3D) culture system has emerged as a promising preclinical model for tumor research owing to its ability to replicate the tissue structure and molecular characteristics of solid tumors in vivo. This system offers several advantages, including high throughput, efficiency, and retention of tumor heterogeneity. Traditional Matrigel-submerged organoid cultures primarily support the long-term proliferation of epithelial cells. One solution for the exploration of the tumor microenvironment is a reconstitution approach involving the introduction of exogenous cell types, either in dual, triple or even multiple combinations. Another solution is a holistic approach including patient-derived tumor fragments, air-liquid interface, suspension 3D culture, and microfluidic tumor-on-chip models. Organoid co-culture models have also gained popularity for studying the tumor microenvironment, evaluating tumor immunotherapy, identifying predictive biomarkers, screening for effective drugs, and modeling infections. By leveraging these 3D culture systems, it is hoped to advance the clinical application of therapeutic approaches and improve patient outcomes.

Multi-gene phylogenetic analyses revealed two novel species and one new record of Trichobotrys (Pleosporales, Dictyosporiaceae) from China.

The rotting wood in freshwater is a unique eco-environment favoring various fungi. During our investigation of freshwater fungi on decaying wood, three hyphomycetes were collected from Jiangxi and Guangxi Provinces, China. Based on the morphological observations and phylogenetic analysis of a combined DNA data containing ITS, LSU, SSU and tef1-α sequences, two new Trichobotrys species, T.meilingensis and T.yunjushanensis, as well as a new record of T.effusa, were introduced. Additionally, a comprehensive description of the genus with both morphological and molecular data was first provided.

3D printing redefines microneedle fabrication for transdermal drug delivery.

Microneedles (MNs) have emerged as an innovative, virtually painless technique for intradermal drug delivery. However, the complex and costly fabrication process has limited their widespread accessibility, especially for individuals requiring frequent drug administration. This study introduces a groundbreaking and cost-effective method for producing MNs utilizing fused deposition modeling (FDM) 3D printing technology to enhance transdermal drug delivery. The proposed fabrication process involves the elongation of molten polylactic acid (PLA) filaments to create meticulously designed conoid and neiloid MNs with smooth surfaces. This study underscores the critical role of printing parameters, particularly extrusion length and printing speed, in determining the shape of the MNs. Notably, the conoid-shaped MNs exhibit exceptional skin-penetrating capabilities. In order to evaluate their effectiveness, the MNs were tested on a polydimethylsiloxane (PDMS) skin model for skin penetration. The results highlight the high potential of 3D-printed MNs for transdermal drug administration. This novel approach capitalizes on the benefits of 3D printing technology to fabricate MNs that hold the promise of transforming painless drug administration for a variety of medical applications.

Development and validation of AI models using LR and LightGBM for predicting distant metastasis in breast cancer: a dual-center study.

Objective: This study aims to develop an artificial intelligence model utilizing clinical blood markers, ultrasound data, and breast biopsy pathological information to predict the distant metastasis in breast cancer patients. Methods: Data from two medical centers were utilized, Clinical blood markers, ultrasound data, and breast biopsy pathological information were separately extracted and selected. Feature dimensionality reduction was performed using Spearman correlation and LASSO regression. Predictive models were constructed using LR and LightGBM machine learning algorithms and validated on internal and external validation sets. Feature correlation analysis was conducted for both models. Results: The LR model achieved AUC values of 0.892, 0.816, and 0.817 for the training, internal validation, and external validation cohorts, respectively. The LightGBM model achieved AUC values of 0.971, 0.861, and 0.890 for the same cohorts, respectively. Clinical decision curve analysis showed a superior net benefit of the LightGBM model over the LR model in predicting distant metastasis in breast cancer. Key features identified included creatine kinase isoenzyme (CK-MB) and alpha-hydroxybutyrate dehydrogenase. Conclusion: This study developed an artificial intelligence model using clinical blood markers, ultrasound data, and pathological information to identify distant metastasis in breast cancer patients. The LightGBM model demonstrated superior predictive accuracy and clinical applicability, suggesting it as a promising tool for early diagnosis of distant metastasis in breast cancer.