The Horizons of Medical Mineralogy: Structure-Bioactivity Relationship and Biomedical Applications of Halloysite Nanoclay.

Medical mineralogy explores the interactions between natural minerals and living organisms such as cells, tissues, and organs and develops therapeutic and diagnostic applications in drug delivery, medical devices, and healthcare materials. Many minerals (especially clays) have been recognized for pharmacological activities and therapeutic potential. Halloysite clay (Chinese medicine name: Chishizhi), manifested as one-dimensional aluminum silicate nanotubes (halloysite nanotubes, HNTs), has gained applications in hemostasis, wound repair, gastrointestinal diseases, tissue engineering, detection and sensing, cosmetics, and daily chemicals formulations. Various biomedical applications of HNTs are derived from hollow tubular structures, high mechanical strength, good biocompatibility, bioactivity, and unique surface characteristics. This natural nanomaterial is safe, abundantly available, and may be processed with environmentally safe green chemistry methods. This review describes the structure and physicochemical properties of HNTs relative to bioactivity. We discuss surface area, porosity and surface defects, hydrophilicity, heterogeneity and charge of external and internal surfaces, as well as biosafety. The paper provides comprehensive guidance for the development of this tubule nanoclay and its advanced biomedical applications for clinical diagnosis and therapy.

Multi-omics analysis reveals that Cas13d contributes to PI3K-AKT signaling and facilitates cell proliferation via PFKFB4 upregulation.

The CRISPR-Cas system is a powerful gene editing technology, the clinical application of which is currently constrained due to safety concerns. A substantial body of safety research concerning Cas9 exists; however, scant attention has been directed toward investigating the safety profile of the emergent Cas13 system, which confers RNA editing capabilities. In particular, uncertainties persist regarding the potential cellular impacts of Cas13d in the absence of reliance on a cleavage effect. In this study, we conducted an initial exploration of the effects of Cas13d on HeLa cells. Total RNA and protein samples were extracted after transfection with a Cas13d-expressing plasmid construct, followed by transcriptomic and proteomic sequencing. Differential gene expression analysis identified 94 upregulated and 847 downregulated genes, while differential protein expression analysis identified 185 upregulated and 231 downregulated proteins. Subsequently, enrichment analysis was conducted on the transcriptome and proteome sequencing data, revealing that the PI3K-Akt signaling pathway is a common term. After intersecting the differentially expressed genes enriched in the PI3K-Akt signaling pathway with all the differentially expressed proteins, it was found that the expression of the related regulatory gene PFKFB4 was upregulated. Moreover, western blot analysis demonstrated that Cas13d can mediate PI3K-Akt signaling upregulation through overexpression of PFKFB4. CCK-8 assay, colony formation, and EdU experiments showed that Cas13d can promote cell proliferation. Our data demonstrate, for the first time, that Cas13d significantly impacts the transcriptomic and proteomic profiles, and proliferation phenotype, of HeLa cells, thus offering novel insights into safety considerations regarding gene editing systems.

Further screening of SNP loci of eggshell translucency related genes and evaluation of genetic effects.

Eggshell translucency is a widespread issue in the field of egg quality. Previous research has established that the heritability of eggshell translucency is relatively low or moderate. Scientists have also successfully identified SNP loci related to eggshell translucency on different chromosomes by using gene chips and single-variant GWAS. However, the specific impact of single or multiple genes on the trait of eggshell translucency remains unknown. In an effort to investigate this, we examined 170 SNPs associated with eggshell translucency obtained by our research group. We selected 966 half-sibling laying hens from 2 generations in 3 pure lines: Dwarf Layer-White, Rhode Island Red-White Strain, and Rhode Island Red. Eggs were collected from each hen over a period of 5 consecutive days, and eggshell translucency was measured using a grading method in which the hens were divided into 2 groups: an opaque group and a translucent group. We collected blood samples from the laying hens and extracted DNA. Time of flight mass spectrometry (TOF-MS) was used for genotyping to identify SNP loci that influence the trait of eggshell translucency. The results of our analysis revealed that using TOF-MS in 3 chicken strains, we were able to eliminate loci with low gene polymorphism, genetic effect contribution less than 1%, and deviation from Hardy-Weinberg equilibrium. Ultimately, 5 SNPs (Affx-50362599, rs15050262, rs312943734, rs316121113, and rs317389181) were identified on chromosomes 1, 5, and 19. Additionally, nine candidate genes (DCN, BTG1, ZFP92, POU2F1, NUCB2, FTL, GGNBP2, ACACA, and TADA2A) were found to be associated with these SNPs. No linkage disequilibrium relationship was observed between the 2 pairs of SNP loci on chromosomes 1 and 19. Based on previous studies on the formation mechanism of eggshell translucency, we hypothesize that NUCB2, FTL, and ACACA genes may be affecting the eggshell structure through different mechanisms, such as increase the water permeability or make thin of eggshell membrane, which promote moisture or part of other egg contents and ultimately lead to the formation of eggshell translucency. These findings validate and identify five SNP loci that regulate the translucency trait, and provide molecular markers for breeding non-translucent populations. Furthermore, this study serves as a reference for further investigation of the genetic regulatory mechanisms underlying eggshell translucency.

Overview of deltamethrin residues and toxic effects in the global environment.

Pyrethroids are synthetic organic insecticides. Deltamethrin, as one of the pyrethroids, has high insecticidal activity against pests and parasites and is less toxic to mammals, and is widely used in cities and urban areas worldwide. After entering the natural environment, deltamethrin circulates between solid, liquid and gas phases and enters organisms through the food chain, posing significant health risks. Increasing evidence has shown that deltamethrin has varying degrees of toxicity to a variety of organisms. This review summarized worldwide studies of deltamethrin residues in different media and found that deltamethrin is widely detected in a range of environments (including soil, water, sediment, and air) and organisms. In addition, the metabolism of deltamethrin, including metabolites and enzymes, was discussed. This review shed the mechanism of toxicity of deltamethrin and its metabolites, including neurotoxicity, immunotoxicity, endocrine disruption toxicity, reproductive toxicity, hepatorenal toxicity. This review is aim to provide reference for the ecological security and human health risk assessment of deltamethrin.

A privacy-preserving platform oriented medical healthcare and its application in identifying patients with candidemia.

Federated learning (FL) has emerged as a significant method for developing machine learning models across multiple devices without centralized data collection. Candidemia, a critical but rare disease in ICUs, poses challenges in early detection and treatment. The goal of this study is to develop a privacy-preserving federated learning framework for predicting candidemia in ICU patients. This approach aims to enhance the accuracy of antifungal drug prescriptions and patient outcomes. This study involved the creation of four predictive FL models for candidemia using data from ICU patients across three hospitals in China. The models were designed to prioritize patient privacy while aggregating learnings across different sites. A unique ensemble feature selection strategy was implemented, combining the strengths of XGBoost's feature importance and statistical test p values. This strategy aimed to optimize the selection of relevant features for accurate predictions. The federated learning models demonstrated significant improvements over locally trained models, with a 9% increase in the area under the curve (AUC) and a 24% rise in true positive ratio (TPR). Notably, the FL models excelled in the combined TPR + TNR metric, which is critical for feature selection in candidemia prediction. The ensemble feature selection method proved more efficient than previous approaches, achieving comparable performance. The study successfully developed a set of federated learning models that significantly enhance the prediction of candidemia in ICU patients. By leveraging a novel feature selection method and maintaining patient privacy, the models provide a robust framework for improved clinical decision-making in the treatment of candidemia.

Seroprevalence survey of Hepatitis E Virus in Domestic Pigs in Guangdong, China.

The Hepatitis E virus (HEV) causes acute and chronic Hepatitis E and is a global public health concern. HEV genotypes 3 (HEV-3) and 4 (HEV-4) are common to humans and animals, and domestic pigs and wild boars have been identified as the main reservoirs. However, limited information is available on the status of HEV infection in pigs, particularly in the Guangdong Province, China. This study aimed to investigate the seroprevalence of HEV in pig farms within the Guangdong Province. A total of 1568 serum samples were collected from 25 farms and tested for anti-HEV IgG antibodies. Enzyme-linked immunosorbent assay (ELISA) results revealed that 57.53% (902/1568) of serum samples from 24 farms (24/25, 96%) were positive for anti-HEV IgG antibodies. Year, season, region, and age were all linked risk factors for HEV in Guangdong, with season and region showing more significant impacts. The results showing a high seroprevalence of HEV confirmed its circulation among domestic pigs in the Guangdong Province, China. The presence of this antibody indicates that HEV infection was or is present on farms, posing a risk of zoonotic transmission of HEV from pigs to exposed workers and from pork or organs to consumption.

Assessment of adverse events of the novel cardiovascular drug vericiguat: a real-world pharmacovigilance study based on FAERS.

BACKGROUND: This study aims to analyze the adverse event reports (AERs) to vericiguat using data from the Food and Drug Administration Adverse Event Reporting System (FAERS) and provide evidence for the clinical use. METHODS: AERs due to vericiguat from 2021Q1 to 2024Q1 identified as the primary suspect were screened, with duplicate reports subsequently eliminated. Various quantitative signal detection methods, including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network, and multi-item gamma poisson shrinker, were then employed for data mining and analysis. Signal strength is represented by the 95% confidence interval, information component (IC), and empirical Bayesian geometric mean (EBGM). RESULTS: A total of 617 vericiguat-related AERs were identified. Strong signals were observed in 21 system organ classes. Furthermore, the most frequently reported preferred terms (PT) was hypotension (n = 86, ROR 25.92, PRR 24.11, IC 4.59, EBGM 24.07), followed by dizziness (n = 52, ROR 6.44, PRR 6.20, IC 2.63, EBGM 6.20), malaise (n = 25, ROR 3.59, PRR 3.54, IC 1.82, EBGM 3.54), blood pressure decreased (n = 23, ROR 20.00, PRR 19.64, IC 4.29, EBGM 19.61), and anemia (n = 21, ROR 6.67, PRR 6.57, IC 2.72, EBGM 6.57). CONCLUSIONS: This study extended the adverse reactions documented in the FDA instruction and provided supplementary evidence regarding the clinical safety of vericiguat.

Integrated machine learning algorithms reveal a bone metastasis-related signature of circulating tumor cells in prostate cancer.

Bone metastasis is an essential factor affecting the prognosis of prostate cancer (PCa), and circulating tumor cells (CTCs) are closely related to distant tumor metastasis. Here, the protein-protein interaction (PPI) networks and Cytoscape application were used to identify diagnostic markers for metastatic events in PCa. We screened ten hub genes, eight of which had area under the ROC curve (AUC) values > 0.85. Subsequently, we aim to develop a bone metastasis-related model relying on differentially expressed genes in CTCs for accurate risk stratification. We developed an integrative program based on machine learning algorithm combinations to construct reliable bone metastasis-related genes prognostic index (BMGPI). On the basis of BMGPI, we carefully evaluated the prognostic outcomes, functional status, tumor immune microenvironment, somatic mutation, copy number variation (CNV), response to immunotherapy and drug sensitivity in different subgroups. BMGPI was an independent risk factor for disease-free survival in PCa. The high risk group demonstrated poor survival as well as higher immune scores, higher tumor mutation burden (TMB), more frequent co-occurrence mutation, and worse efficacy of immunotherapy. This study highlights a new prognostic signature, the BMGPI. BMGPI is an independent predictor of prognosis in PCa patients and is closely associated with the immune microenvironment and the efficacy of immunotherapy.

Genetic Causality between Type 1 Diabetes and Arrhythmia Identified by a Two-sample Mendelian Randomization Study.

BACKGROUND: Clinical studies have shown that cardiovascular diseases in patients with type 1 diabetes (T1D) are often atypical or asymptomatic. The link between T1D and arrhythmia remains unclear. To infer causality between T1D and arrhythmia at the genetic level, we conducted a Mendelian randomization study through the genetic tools of T1D. METHODS: In this study, we used genetic variables and summary statistics from genome-wide association studies of T1D and arrhythmia. Single nucleotide polymorphisms were selected based on the assumptions of instrumental variables. The inverse variance-weighted method was used as the primary analysis to summarize the causal effects between exposure and outcome. The weighted median and weighted mode methods were used as secondary methods. We tested for horizontal pleiotropy using the MR-Egger method and detected heterogeneity using the Q-test. A leave-one-out sensitivity analysis was performed. Scatter plots, forest plots, and funnel plots were used to visualize the results of the MR analysis. RESULTS: In this study, we selected 28 T1D-related SNPs as instrumental variables. The IVW [odds ratio (OR) = 0.98, 95 % confidence interval (CI) = 0.97-1.00, P = 0.008], weighted median (OR = 0.98, 95 % CI = 0.96 - 0.99, P = 0.009), and weighted mode (OR = 0.98, 95 % CI = 0.96-0.99, P = 0.018) analysis methods suggested a causal effect of T1D on arrhythmia. The MR-Egger method indicated no horizontal pleiotropy (P = 0.649), and the Q-test showed no heterogeneity (IVW, P = 0.653). CONCLUSIONS: Our MR analysis revealed a causal association between T1D and the development of arrhythmia, indicating that patients with T1D had a higher risk of arrhythmia.

Downregulation of HIGD1B induces mitochondria-mediated apoptosis in gastric cancer cells by inactivating Akt and ERK pathways.

Gastric cancer (GC) is one of the most common malignancies worldwide. Hypoxia-inducible domain (HIGD) family members (e.g., HIGD1A) have been linked to tumor progression. However, the role of HIGD1B (another HIGD family member) in GC has yet to be fully understood. Based on data from TCGA_GC, GSE65801, and GSE65801 data sets, HIGD1B levels were evaluated in normal and GC tissues. Next, HIGD1B levels were validated by reverse transcription-quantitative PCR and western blot analysis analyses. Meanwhile, patients with GC in the TCGA_GC cohort were grouped into high- and low-HIGD1B level groups, and overall survival, functional enrichment, and immune infiltration were analyzed. Additionally, gain- and loss-of-function experiments were performed to determine the function of HIGD1B in GC cells. Compared to normal controls, HIGD1B mRNA levels were significantly elevated in GC tissues. Moreover, high HIGD1B levels may be an independent indicator of poor prognosis in patients with GC. Additionally, high HIGD1B levels were correlated with high stromal and ESTIMATE scores and elevated expression of immune checkpoints in patients with GC. Functional analyses showed that HIGD1B deficiency notably suppressed GC cell proliferation, migration, and invasion. Moreover, HIGD1B deficiency significantly induced mitochondria-mediated apoptosis in GC cells by inactivating Akt and ERK pathways. Collectively, HIGD1B may predict the prognosis of patients with GC and may function as an oncogene in GC. These findings suggest that HIGD1B may serve as a prognostic biomarker and potential therapeutic target in GC.

Metal-Organic Framework-Based Surface-Enhanced Raman Scattering Sensing Platform for Trace Malondialdehyde Detection in Tears.

Disease biomarkers in tears are crucial for clinical diagnosis and health monitoring. However, the limited volume of tear samples, low concentration of tear biomarkers, and complex tear composition present challenges for precise testing. We introduce a spot-on testing platform of metal-organic framework (MOF)-based surface-enhanced Raman scattering (SERS) capillary column, which is capable of target molecules selective separation and enrichment for tear biomarkers in situ detection. It consists of Au nanostars for effective SERS signal and a porous MOF shell for separating impurities through molecular sieving effect. This platform allows for simultaneous collection and detection of tear, capturing the disease biomarker malondialdehyde in tears with a 9.38 × 10-9 mol/L limit of detection. Moreover, we designed a hand-held device based on this tubular SERS sensor, successfully diagnosing patients with dry eye disease. This functional capillary column enables noninvasive and rapid diagnosis of biomarkers in biofluids, providing potential for disease diagnosis and healthcare monitoring.

Ultrafast Photoexcitation Induced Passivation for Quasi-2D Perovskite Photodetectors.

Quasi-2D perovskites exhibit great potential in photodetectors due to their exceptional optoelectronic responsivity and stability, compared to their 3D counterparts. However, the defects are detrimental to the responsivity, response speed, and stability of perovskite photodetectors. Herein, an ultrafast photoexcitation-induced passivation technique is proposed to synergistically reduce the dimensionality at the surface and induce oxygen doping in the bulk, via tuning the photoexcitation intensity. At the optimal photoexcitation level, the excited electrons and holes generate stretching force on the Pb─I bonds at the interlayered [PbI6]-, resulting in low dimensional perovskite formation, and the absorptive oxygen is combined with I vacancies at the same time. These two induced processes synergistically boost the carrier transport and interface contact performance. The most outstanding device exhibits a fast response speed with rise/decay time of 201/627 ns, with a peak responsivity/detectivity of 163 mA W-1/4.52 × 1010 Jones at 325 nm and the enhanced cycling stability. This work suggests the possibility of a new passivation technique for high performance 2D perovskite optoelectronics.

Loneliness, functional disability and lower urinary tract symptoms suggestive of benign prostatic hyperplasia in aging men: Insights from the China health and retirement longitudinal study.

BACKGROUND: Research has demonstrated that social isolation and loneliness are linked to functional disability in older adults. With the intensification of global aging, functional disability and lower urinary tract symptoms suggestive of benign prostatic hyperplasia (LUTS/BPH) have become common public health issues affecting elderly men. METHODS: This study utilized data from the CHARLS database. The functional status of participants was evaluated through activities of daily living (ADL) and instrumental activities of daily living (IADL). Logistic regression analyses were employed to investigate variables associated with LUTS/BPH. RESULTS: Univariate logistic regression revealed associations between loneliness (OR: 1.26; 95 % CI: 1.08-1.46) (excluding social isolation), ADL (OR: 2.17; 95 % CI: 1.86-2.52), IADL disability (OR: 1.37; 95 % CI: 1.16-1.60), and LUTS/BPH. Following rigorous adjustment for potential confounding factors, it was determined that ADL disability independently correlated with LUTS/BPH (OR: 1.92; 95 % CI: 1.17-3.17). CONCLUSION: ADL disability is significantly linked to an elevated risk of LUTS/BPH in Chinese elderly men. These findings enhance our understanding of the relationship between functional status and LUTS/BPH.

A Triboelectric-Electromagnetic Hybrid Nanogenerator with Magnetic Coupling Assisted Waterproof Encapsulation for Long-Lasting Energy Harvesting.

Ocean energy harvesting based on a triboelectric nanogenerator (TENG) has great application potential, while the encapsulation of triboelectric devices in water poses a critical issue. Herein, a triboelectric-electromagnetic hybrid nanogenerator (TE-HNG) consisting of TENGs and electromagnetic generators (EMGs) is proposed to harvest water flow energy. A magnetic coupling transmission component is applied to replace traditional bearing structures, which can realize the fully enclosed packaging of the TENG devices and achieve long-lasting energy harvesting from water flow. Under the intense water impact, magnetic coupling reduces the possibility of internal gear damage due to excessive torque, indicating superior stability and robustness compared to conventional TENG. At the waterwheel rotates speed of 75 rpm, the TE-HNG can generate an output peak power of 114.83 mW, corresponding to a peak power density of 37.105 W m-3. After 5 h of continuous operation, the electrical output attenuation of TENG is less than 3%, demonstrating excellent device durability. Moreover, a self-powered temperature sensing system and a self-powered cathodic protection system based on the TE-HNG are developed and illustrated. This work provides a prospective strategy for improving the output stability of TENGs, which benefits the practical applications of the TENGs in large-scale blue energy harvesting.

Ultra-High Proportion of Grain Boundaries in Zinc Metal Anode Spontaneously Inhibiting Dendrites Growth.

Aqueous Zn-ion batteries are an attractive electrochemical energy storage solution for their budget and safe properties. However, dendrites and uncontrolled side reactions in anodes detract the cycle life and energy density of the batteries. Grain boundaries in metals are generally considered as the source of the above problems but we present a diverse result. This study introduces an ultra-high proportion of grain boundaries on zinc electrodes through femtosecond laser bombardment to enhance stability of zinc metal/electrolyte interface. The ultra-high proportion of grain boundaries promotes the homogenization of zinc growth potential, to achieve uniform nucleation and growth, thereby suppressing dendrite formation. Additionally, the abundant active sites mitigate the side reactions during the electrochemical process. Consequently, the 15 µm Fs-Zn||MnO2 pouch cell achieves an energy density of 249.4 Wh kg-1 and operates for over 60 cycles at a depth-of-discharge of 23 %. The recognition of the favorable influence exerted by UP-GBs paves a new way for other metal batteries.

Mn(II)-Based Metal Halide with Near-Unity Quantum Yield for White LEDs and High-Resolution X-ray Imaging.

Metal halides have drawn great interest as luminescent materials and scintillators due to their outstanding optical properties. Exploring new types of phosphors with easy production processes, excellent photophysical properties, high light yields, and environmentally friendly compositions is crucial and quite challenging. Herein, a novel Mn(II)-based metal halide (4-BTP)2MnBr4 was produced using a facile solvent evaporation method, which exhibited a strong green emission peaking at 524 nm from the d-d transition of tetrahedral-coordinated Mn2+ ion and a near-unity quantum yield. The prepared white light-emitting diode device has a wide color gamut of 100.7% NTSC with CIE chromaticity coordinates of (0.32, 0.32). In addition, (4-BTP)2MnBr4 demonstrates excellent characteristics in X-ray scintillation, including a high light yield of 98 000 photons/MeV, a sensitive detection limit of 37.4 nGy/s, excellent resistance to radiation damage, and successful demonstration of X-ray imaging with high resolution at 21.3 lp/mm, revealing the potential for application in diagnostic X-ray medical imaging and industry radiation detection.

Accessing Early Differentiation of Virus-Specific Follicular Helper CD4+ T Cell in Acute LCMV-Infected Mice.

Follicular Helper T (TFH) cells are perceived as an independent CD4+ T cell lineage that assists cognate B cells in producing high-affinity antibodies, thus establishing long-term humoral immunity. During acute viral infection, the fate commitment of virus-specific TFH cells is determined in the early infection phase, and investigations of the early-differentiated TFH cells are crucial in understanding T cell-dependent humoral immunity and optimizing vaccine design. In the study, using a mouse model of acute lymphocytic choriomeningitis virus (LCMV) infection and the TCR-transgenic SMARTA (SM) mouse with CD4+ T cells specifically recognizing LCMV glycoprotein epitope I-AbGP66-77, we described procedures to access the early fate commitment of virus-specific TFH cells based on flow cytometry stainings. Furthermore, by exploiting retroviral transduction of SM CD4+ T cells, methods to manipulate gene expression in early-differentiated virus-specific TFH cells are also provided. Hence, these methods will help in studies exploring the mechanism(s) underlying the early commitment of virus-specific TFH cells.

ProMENDA: an updated resource for proteomic and metabolomic characterization in depression.

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

A New Dataset and Comparative Study for Aphid Cluster Detection and Segmentation in Sorghum Fields.

Aphid infestations are one of the primary causes of extensive damage to wheat and sorghum fields and are one of the most common vectors for plant viruses, resulting in significant agricultural yield losses. To address this problem, farmers often employ the inefficient use of harmful chemical pesticides that have negative health and environmental impacts. As a result, a large amount of pesticide is wasted on areas without significant pest infestation. This brings to attention the urgent need for an intelligent autonomous system that can locate and spray sufficiently large infestations selectively within the complex crop canopies. We have developed a large multi-scale dataset for aphid cluster detection and segmentation, collected from actual sorghum fields and meticulously annotated to include clusters of aphids. Our dataset comprises a total of 54,742 image patches, showcasing a variety of viewpoints, diverse lighting conditions, and multiple scales, highlighting its effectiveness for real-world applications. In this study, we trained and evaluated four real-time semantic segmentation models and three object detection models specifically for aphid cluster segmentation and detection. Considering the balance between accuracy and efficiency, Fast-SCNN delivered the most effective segmentation results, achieving 80.46% mean precision, 81.21% mean recall, and 91.66 frames per second (FPS). For object detection, RT-DETR exhibited the best overall performance with a 61.63% mean average precision (mAP), 92.6% mean recall, and 72.55 on an NVIDIA V100 GPU. Our experiments further indicate that aphid cluster segmentation is more suitable for assessing aphid infestations than using detection models.

A bidirectional causal relationship study between mental disorders and male and female infertility.

Background: The relation between mental disorders (MDs) and infertility can be reciprocal. But exactly which MD affects infertility remains controversial. Our aim was to use Mendelian randomization (MR) to explore bidirectional causality between 15 MDs and male infertility and female infertility. Methods: The data of MDs, male infertility, and female infertility were derived from published genome-wide association studies (GWAS). The inverse variance weighted method was considered to be the main analytical approach. Sensitivity analysis was performed using MR-Egger, Cochran's Q, radial MR, and MR-PRESSO tests. Results: Our results found that mood disorders (OR, 1.4497; 95% CI, 1.0093 - 2.0823; P = 0.0444) and attention deficit hyperactivity disorder (OR, 1.3921; 95% CI, 1.0943 - 1.7709; P = 0.0071) were positively correlated with male infertility, but obsessive-compulsive disorder (OR, 0.8208; 95% CI, 0.7146 - 0.9429; P = 0.0052) was negatively associated with male infertility. For females, anorexia nervosa (OR, 1.0898; 95% CI, 1.0070 - 1.1794; P = 0.0329), attention deficit hyperactivity disorder (OR, 1.1013; 95% CI, 1.0041 - 1.2079; P = 0.0406), and major depressive disorder (OR, 1.1423; 95% CI, 1.0213 - 1.2778; P = 0.0199) increased risk of infertility. In reverse relationship, female infertility increased the incidence of bipolar disorder (OR, 1.0009; 95% CI, 1.0001 - 1.0017; P = 0.0281). Conclusion: We demonstrated the association between five MDs and male or female infertility. Female infertility was also found to be associated with an increased risk of one MD. We look forward to better designed epidemiological studies to support our results.