Plin4 exacerbates cadmium-decreased testosterone level via inducing ferroptosis in testicular Leydig cells.

Strong evidence indicates that environmental stressors are the risk factors for male testosterone deficiency (TD). However, the mechanisms of environmental stress-induced TD remain unclear. Based on our all-cause male reproductive cohort, we found that serum ferrous iron (Fe2⁺) levels were elevated in TD donors. Then, we explored the role and mechanism of ferroptosis in environmental stress-reduced testosterone levels through in vivo and in vitro models. Data demonstrated that ferroptosis and lipid droplet deposition were observed in environmental stress-exposed testicular Leydig cells. Pretreatment with ferrostatin-1 (Fer-1), a specific ferroptosis inhibitor, markedly mitigated environmental stress-reduced testosterone levels. Through screening of core genes involved in lipid droplets formation, it was found that environmental stress significantly increased the levels of perilipins 4 (PLIN4) protein and mRNA in testicular Leydig cells. Further experiments showed that Plin4 siRNA reversed environmental stress-induced lipid droplet deposition and ferroptosis in Leydig cells. Additionally, environmental stress increased the levels of METTL3, METTL14, and total RNA m6A in testicular Leydig cells. Mechanistically, S-adenosylhomocysteine, an inhibitor of METTL3 and METTL14 heterodimer activity, restored the abnormal levels of Plin4, Fe2⁺ and testosterone in environmental stress-treated Leydig cells. Collectively, these results suggest that Plin4 exacerbates environmental stress-decreased testosterone level via inducing ferroptosis in testicular Leydig cells.

Utilizing multiclassifier radiomics analysis of ultrasound to predict high axillary lymph node tumour burden in node-positive breast cancer patients: a multicentre study.

BACKGROUND: The tumor burden within the axillary lymph nodes (ALNs) constitutes a pivotal factor in breast cancer, serving as the primary determinant for treatment decisions and exhibiting a close correlation with prognosis. OBJECTIVE: This study aimed to investigate the potential of ultrasound-based radiomics and clinical characteristics in non-invasively distinguishing between low tumor burden (1-2 positive nodes) and high tumor burden (more than 2 positive nodes) in patients with node-positive breast cancer. METHODS: A total of 215 patients with node-positive breast cancer, who underwent preoperative ultrasound examinations, were enrolled in this study. Among these patients, 144 cases were allocated to the training set, 37 cases to the validation set, and 34 cases to the testing set. Postoperative histopathology was used to determine the status of ALN tumor burden. The region of interest for breast cancer was delineated on the ultrasound image. Nine models were developed to predict high ALN tumor burden, employing a combination of three feature screening methods and three machine learning classifiers. Ultimately, the optimal model was selected and tested on both the validation and testing sets. In addition, clinical characteristics were screened to develop a clinical model. Furthermore, Shapley additive explanations (SHAP) values were utilized to provide explanations for the machine learning model. RESULTS: During the validation and testing sets, the models demonstrated area under the curve (AUC) values ranging from 0.577 to 0.733 and 0.583 to 0.719, and accuracies ranging from 64.9% to 75.7% and 64.7% to 70.6%, respectively. Ultimately, the Boruta_XGB model, comprising five radiomics features, was selected as the final model. The AUC values of this model for distinguishing low from high tumor burden were 0.828, 0.715, and 0.719 in the training, validation, and testing sets, respectively, demonstrating its superiority over the clinical model. CONCLUSIONS: The developed radiomics models exhibited a significant level of predictive performance. The Boruta_XGB radiomics model outperformed other radiomics models in this study.

Phage-induced "one-to-many" FRET sensor for highly sensitive detection of Escherichia coli O157:H7.

As a foodborne pathogen capable of causing severe illnesses, early detection of Escherichia coli O157:H7 (E. coli O157:H7) is crucial for ensuring food safety. While Förster resonance energy transfer (FRET) is an efficient and precise detection technique, there remains a need for amplification strategies to detect low concentrations of E. coli O157:H7. In this study, we presented a phage (M13)-induced "one to many" FRET platform for sensitively detecting E. coli O157:H7. The aptamers, which specifically recognize E. coli O157:H7 were attached to magnetic beads as capture probes for separating E. coli O157:H7 from food samples. The peptide O157S, which specifically targets E. coli O157:H7, and streptavidin binding peptide (SBP), which binds to streptavidin (SA), were displayed on the P3 and P8 proteins of M13, respectively, to construct the O157S-M13K07-SBP phage as a detection probe for signal output. Due to the precise distance (≈3.2 nm) between two neighboring N-terminus of P8 protein, the SA-labeled FRET donor and acceptor can be fixed at the Förster distance on the surface of O157S-M13K07-SBP via the binding of SA and SBP, inducing FRET. Moreover, the P8 protein, with ≈2700 copies, enabled multiple FRET (≈605) occurrences, amplifying FRET in each E. coli O157:H7 recognition event. The O157S-M13K07-SBP-based FRET sensor can detect E. coli O157:H7 at concentration as low as 6 CFU/mL and demonstrates excellent performance in terms of selectivity, detection time (≈3 h), accuracy, precision, practical application, and storage stability. In summary, we have developed a powerful tool for detecting various targets in food safety, environmental monitoring, and medical diagnosis.

CentIER: accurate centromere identification for plant genome.

This paper introduces CentIER, the first bioinformatic tool designed to detect complete centromeric regions without additional wet experiments. The accuracy of CentIER was validated on diverse plant genomes such as Arabidopsis, rice, maize and mulberry, and the results show that CentIER can perform significantly more complete and accurate detection than the existing tool.

The role of HnrnpF/H as a driver of oligoteratozoospermia.

Male subfertility or infertility is a common condition often characterized by men producing a low number of sperm with poor quality. To gain insight into this condition, we performed a quantitative proteomic analysis of semen samples obtained from infertile and fertile men. At least 6 proteins showed significant differences in regulation of alternatively spliced isoforms. To investigate this link between aberrant alternative splicing and production of poor-quality spermatozoa, we overexpressed the hnrnpH/F-orthologue Glorund (Glo) in Drosophila, which was also found to be abundant in poor quality human sperm. Transgenic animals produced low numbers of morphologically defective spermatozoa and aberrant formation of the "dense body," an organelle akin to the mammalian manchette. Furthermore, fertility trials demonstrated that transgenic flies were either completely infertile or highly subfertile. These findings suggest that dysregulation of hnrnpH/F is likely to result in the production of low-quality semen, leading to subfertility or infertility in men.

Development and validation of a prognostic nomogram to predict 30-day all-cause mortality in patients with CRO infection treated with colistin sulfate.

Background: Carbapenem-resistant Gram-negative organism (CRO) infection is a critical clinical disease with high mortality rates. The 30-day mortality rate following antibiotic treatment serves as a benchmark for assessing the quality of care. Colistin sulfate is currently considered the last resort therapy against infections caused by CRO. Nevertheless, there is a scarcity of reliable tools for personalized prognosis of CRO infections. This study aimed to develop and validate a nomogram to predict the 30-day all-cause mortality in patients with CRO infection who underwent colistin sulfate treatment. Methods: A prediction model was developed and preliminarily validated using CRO-infected patients treated with colistin sulfate at Tongji Hospital in Wuhan, China, who were hospitalized between May 2018 and May 2023, forming the study cohort. Patients admitted to Xianning Central Hospital in Xianning, China, between May 2018 and May 2023 were considered for external validation. Multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of 30-day all-cause mortality. The receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and the calibration curve were used to evaluate model performance. The decision curve analysis (DCA) was used to assess the model clinical utility. Results: A total of 170 patients in the study cohort and 65 patients in the external validation cohort were included. Factors such as age, duration of combination therapy, nasogastric tube placement, history of previous surgery, presence of polymicrobial infections, and occurrence of septic shock were independently associated with 30-day all-cause mortality and were used to construct the nomogram. The AUC of the nomogram constructed from the above six factors was 0.888 in the training set. The Hosmer-Lemeshow test showed that the model was a good fit (p = 0.944). The calibration curve of the nomogram was close to the ideal diagonal line. Furthermore, the decision curve analysis demonstrated significantly better net benefit in the model. The external validation proved the reliability of the prediction nomogram. Conclusion: A nomogram was developed and validated to predict the occurrence of 30-day all-cause mortality in patients with CRO infection treated with colistin sulfate. This nomogram offers healthcare providers a precise and efficient means for early prediction, treatment management, and patient notification in cases of CRO infection treated with colistin sulfate.

Changes of cerebral structure and perfusion in subtypes of systemic sclerosis: a brain magnetic resonance imaging study.

OBJECTIVES: The characteristics of brain impairment in different subtypes of systemic sclerosis (SSc) (dcSSc, diffuse cutaneous SSc; lcSSc, limited cutaneous SSc) remain unclear. This study aimed to characterize cerebral structure and perfusion changes in different subtype of SSc patients using magnetic resonance (MR) imaging. METHODS: Seventy SSc patients (46.0 ± 11.7 years, 62 females) and 30 healthy volunteers (44.8 ± 13.7 years, 24 females) were recruited and underwent brain MR imaging and Montreal Cognitive Assessment (MoCA) test. Gray matter (GM) volumes were measured using voxel-based morphometry analysis on T1-weighted images. Voxel-based and regional cerebral blood flow (CBF) was calculated on arterial spin labelling images. The cerebral structural and perfusion measurements by MR imaging were compared among dcSSc, lcSSc and healthy subjects using one-way ANOVA. The correlations between clinical characteristics and MR imaging measurements were also analyzed. RESULTS: The dcSSc patients exhibited a significant reduction in GM volume in the para-hippocampal region (cluster p < 0.01, FWE corrected) compared with healthy volunteers. Whereas, SSc patients, particularly lcSSc patients, showed elevated CBF in cerebellum, insula, cerebral cortex, and subcortical structures (regional analyses: all p < 0.05; voxel-based analyses: cluster p < 0.01, FWE corrected). Furthermore, clinical characteristics of modified Rodnan skin score (mRSS) (r value ranged from -0.29 to -0.45), MoCA scores (r = 0.40) and antinuclear antibody (ANA) positivity (r=-0.33) were significantly associated with CBF in some regions (all p < 0.05). CONCLUSION: The manifestations of brain involvement vary among different subtypes of SSc. In addition, severe skin sclerosis may indicate higher risk of brain involvement in SSc patients.

[Influence of gingival biotype width on the health of peri-implant bone and soft tissues and the aesthetic outcome of the gingival papilla for single maxillary posterior implants].

PURPOSE: To explore the influence of gingival biotype and width of keratinized gingiva on peri-implant bone tissue, soft tissue health, and esthetic outcome of the papilla surrounding single posterior maxillary implants. METHODS: Seventy-eight patients who underwent single posterior maxillary implant surgery from May 2019 to September 2022 were selected, involving the placement of 78 implants. Based on periodontal probing outcomes one month post-restoration, the patients were divided into thin gingival biotype group(n=32) and thick gingival biotype group(n=46). Comparisons were made six months after implant restoration regarding buccal keratinized mucosa width(KMW), peri-implant bone tissue [implant bone loss(IBL)], soft tissue health [modified plaque index (mPLI), modified bleeding index for implants (mBLI), probing pocket depth (PPD)], and esthetic effect of the papilla [papilla index score (PIS), food impaction, gingival margin color satisfaction index (GMCS)]. Statistical analysis was performed with SPSS 27.0 software package. RESULTS: The thick gingival biotype group showed significantly greater keratinized gingival width compared to the thin gingival biotype group (P＜0.05). Spearman correlation analysis revealed a positive correlation between gingival biotype and keratinized gingival width(r=-0.416, P=0.000). For peri-implant bone tissue, bone loss in the thin gingival biotype group was significantly higher than that in the thick gingival biotype group. In soft tissue health, the probing pocket depth for implants in the thin gingival biotype group was significantly less than that in the thick gingival biotype group. In terms of esthetic effect of the papilla, PES score in the thin gingival biotype group was significantly lower than in the thick gingival biotype group(P＜0.05). Pearson correlation analysis showed a negative correlation between gingival biotype and papilla index score, GMCS, bleeding on probing, and PPD, but a positive correlation with food impaction, bone loss and mPLI(P＜0.05). The width of keratinized gingiva was positively correlated with papilla index score, GMCS, bleeding on probing and PPD, but negatively correlated with food impaction, bone loss and mPLI(P＜0.05). There was significantly difference between thin and thick gingival biotype groups for KMW >2 mm(P＜0.05). A significant difference was showed in thick gingival biotype group when KMW ≤2 mm and ＞2 mm(P＜0.05). CONCLUSIONS: Gingival biotype and keratinized mucosa width significantly influence peri-implant bone and soft tissue health as well as esthetic outcome of the papilla around single posterior maxillary implants, offering guidance for predicting the long-term success and esthetic outcomes of implants.

Counterintuitive Trend of Intrusion Pressure with Temperature in the Hydrophobic Cu2(tebpz) MOF.

Liquid porosimetry experiments reveal a peculiar trend of the intrusion pressure of water in hydrophobic Cu2(3,3',5,5'-tetraethyl-4,4'-bipyrazolate) MOF. At lower temperature (T) range, the intrusion pressure (Pi) increases with T. For higher T values, Pi first reaches a maximum and then decreases. This is at odds with the Young-Laplace law, which for systems showing a continuous decrease of contact angle with T predicts a corresponding reduction of the intrusion pressure. Though the Young-Laplace law is not expected to provide quantitative predictions at the subnanoscale of Cu2(tebpz) pores, the physical intuition suggests that to a reduction of their hydrophobicity corresponds a reduction of the Pi. Molecular dynamics simulations and sychrothron experiments allowed to clarify the mechanism of the peculiar trend of Pi with T. At increasing temperatures the vapor density within the MOF' pores grows significantly, bringing the corresponding partial pressure to ≈5 MPa. This pressure, which is consistent with the shift of Pi observed in liquid porosimetry, represents a threshold to be overcame before intrusion takes place. Beyond some value of temperature, the phenomenon of reduction of hydrophobicity (and water surface tension) dominated over the opposite effect of increase of vapor pressure and Pi inverts its trend with T.

Biomedical potentials of alginate via physical, chemical, and biological modifications.

Alginate is a linear polysaccharide with a modifiable structure and abundant functional groups, offers immense potential for tailoring diverse alginate-based materials to meet the demands of biomedical applications. Given the advancements in modification techniques, it is significant to analyze and summarize the modification of alginate by physical, chemical and biological methods. These approaches provide plentiful information on the preparation, characterization and application of alginate-based materials. Physical modification generally involves blending and physical crosslinking, while chemical modification relies on chemical reactions, mainly including acylation, sulfation, phosphorylation, carbodiimide coupling, nucleophilic substitution, graft copolymerization, terminal modification, and degradation. Chemical modified alginate contains chemically crosslinked alginate, grafted alginate and oligo-alginate. Biological modification associated with various enzymes to realize the hydrolysis or grafting. These diverse modifications hold great promise in fully harnessing the potential of alginate for its burgeoning biomedical applications in the future. In summary, this review provides a comprehensive discussion and summary of different modification methods applied to improve the properties of alginate while expanding its biomedical potentials.

IRnet: Immunotherapy response prediction using pathway knowledge-informed graph neural network.

INTRODUCTION: Immune checkpoint inhibitors (ICIs) are potent and precise therapies for various cancer types, significantly improving survival rates in patients who respond positively to them. However, only a minority of patients benefit from ICI treatments. OBJECTIVES: Identifying ICI responders before treatment could greatly conserve medical resources, minimize potential drug side effects, and expedite the search for alternative therapies. Our goal is to introduce a novel deep-learning method to predict ICI treatment responses in cancer patients. METHODS: The proposed deep-learning framework leverages graph neural network and biological pathway knowledge. We trained and tested our method using ICI-treated patients' data from several clinical trials covering melanoma, gastric cancer, and bladder cancer. RESULTS: Our results demonstrate that this predictive model outperforms current state-of-the-art methods and tumor microenvironment-based predictors. Additionally, the model quantifies the importance of pathways, pathway interactions, and genes in its predictions. A web server for IRnet has been developed and deployed, providing broad accessibility to users at https://irnet.missouri.edu. CONCLUSION: IRnet is a competitive tool for predicting patient responses to immunotherapy, specifically ICIs. Its interpretability also offers valuable insights into the mechanisms underlying ICI treatments.

FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants.

FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa. Furthermore, the platform includes machine-learning based methods and navigation tools designed to aid in characterizing metabolic pathways and protein interactions. Comprehensive gene and protein information cards, a Basic Local Alignment Search Tool search function, similar structure search capacities from AphaFold, and ChatGPT-based query for protein information are additional features. Database URL: https://www.fatplants.net/.

Risk factors for pathological upgrading and noncurative resection in patients with gastric mucosal lesions after endoscopic submucosal dissection.

BACKGROUND: The pathological results obtained from endoscopic forceps biopsy (EFB) do not always align with the findings of postoperative endoscopic submucosal dissection (ESD). Furthermore, as ESD becomes more widespread, the number of noncurative endoscopic cases increases; thus, an accurate preoperative diagnosis and an appropriate treatment method are crucial. The purpose of this study was to explore the risk factors for postoperative pathological upgrading and noncurative resection and to gather experience in clinical and pathological diagnosis. METHODS: From March 2016 to November 2023, 292 ESD specimens were collected from 262 patients with gastric mucosal lesions. Clinicopathological information, the coincidence rate of pathological diagnosis between EFB and ESD specimens, and risk factors related to noncurative resection were analyzed retrospectively. RESULTS: The overall upgraded pathological diagnosis rate between EFB and ESD was 26.4%. The independent predictors for the upgraded group included proximal stomach lesions, lesion size > 2 cm, surface ulceration, and surface nodules. Twenty of the 235 early gastric cancer (EGC) patients underwent noncurative ESD resection. Multivariate analysis showed that undifferentiated carcinoma and tumor infiltration into the submucosa were significantly associated with noncurative resection. CONCLUSION: Biopsy cannot fully represent the lesions of gastric intraepithelial neoplasia (GIN). When a suspected epithelial dysplasia is suspected, a careful endoscopic examination should be conducted to evaluate the lesion site, size, and surface characteristics to ensure an accurate diagnosis. Noncurative endoscopic resection is associated with undifferentiated carcinoma and submucosal infiltration. Clinicians must be familiar with these predictive factors for noncurative resection and select the appropriate treatment for their patients.

Heterosis formation mechanism, prediction methods, and their application and prospect in pig production.

Heterosis is the phenomenon that the hybrid offspring outperform two-parent population. Hybridisation has been widely used in plant and animal production as it effectively improves the growth and developmental performance, reproductive performance and disease resistance of the offspring. Hybridization can effectively improve the growth and development performance, reproductive performance and disease resistance of offspring, so it is widely used in animal and plant production. Researchers have used cross-breeding techniques to cultivate excellent new agricultural and animal husbandry strains and supporting lines such as super-excellent Chaoyou 1000 hybrid rice, Xiaoyan No.6 hybrid wheat, Dumeng sheep, and Shanxia black pigs. However, there are still some urgent problems in the current hybrid dominance research: the existing hybrid dominance theory can only partially explain the phenomenon of plant and animal hybrid dominance, and the theory of animal hybrid dominance is less researched, and the accuracy of the existing hybrid dominance prediction methods is limited. China is the world's largest pork production and consumption country. Heterosis can effectively improve the production performance of pigs, and its application in the pig industry has important economic and research value. However, the existing research on pig hybrid production is in its infancy and needs to be further studied. In this review, we summarize the existing heterosis theory, heterosis prediction methods, and their application in pig production, to provide a reference for the application of heterosis in pig breeding.

Multiple Stimuli-Responsive Color-Changing Polymer Materials for Reversible Writing and Anti-Counterfeiting.

Polymer materials with multiple stimuli-responsive properties have demonstrated many potential and practical applications. By covalently introducing spiropyran (SP1) and spirothiopyran (STP) into the polyurethane backbone, photochromic, mechanochromic, and thermally discolored polymer materials have been prepared. In this work, we report for the first time that white light (violet, blue, and green light) above a certain intensity can activate STP to green color. Based on the above discovery, the polyurethane with SP1 and STP can exhibit reversible three-color changes (brown, green, and purple) in response to four stimuli: ultraviolet irradiation, white light irradiation, mechanical stress, and heat. The color-changing polymer materials have high color contrast and excellent reversibility, and can be used for reversible writing, anticounterfeiting and information encryption, etc.

Contactin -Associated protein1 Regulates Autophagy by Modulating the PI3K/AKT/mTOR Signaling Pathway and ATG4B Levels in Vitro and in Vivo.

Contactin-associated protein1 (Caspr1) plays an important role in the formation and stability of myelinated axons. In Caspr1 mutant mice, autophagy-related structures accumulate in neurons, causing axonal degeneration; however, the mechanism by which Caspr1 regulates autophagy remains unknown. To illustrate the mechanism of Caspr1 in autophagy process, we demonstrated that Caspr1 knockout in primary neurons from mice along with human cell lines, HEK-293 and HeLa, induced autophagy by downregulating the PI3K/AKT/mTOR signaling pathway to promote the conversion of microtubule-associated protein light chain 3 I (LC3-I) to LC3-II. In contrast, Caspr1 overexpression in cells contributed to the upregulation of this signaling pathway. We also demonstrated that Caspr1 knockout led to increased LC3-I protein expression in mice. In addition, Caspr1 could inhibit the expression of autophagy-related 4B cysteine peptidase (ATG4B) protein by directly binding to ATG4B in overexpressed Caspr1 cells. Intriguingly, we found an accumulation of ATG4B in the Golgi apparatuses of cells overexpressing Caspr1; therefore, we speculate that Caspr1 may restrict ATG4 secretion from the Golgi apparatus to the cytoplasm. Collectively, our results indicate that Caspr1 may regulate autophagy by modulating the PI3K/AKT/mTOR signaling pathway and the levels of ATG4 protein, both in vitro and in vivo. Thus, Caspr1 can be a potential therapeutic target in axonal damage and demyelinating diseases.

Neo-5,10-seco-clerodane diterpenoids from Schnabelia terniflora.

Three new neo-5,10-seco-clerodane diterpenoids (1-3), four previously undescribed ethoxy/methoxy acetal analogues (4-7), one new etherified labdane diterpenoid (8), and seven known diterpenoids (9-15) were isolated from the whole plant of Schnabelia terniflora. Their structures were established on the basis of extensive spectroscopic analysis, single-crystal X-ray diffraction data, calculated electronic circular dichroism (ECD), and Mo2(OAc)4-induced circular dichroism. Compounds 2 and 3 represent the first examples of neo-5,10-seco-clerodane diterpenoids containing a 1H-pyrrole-2,5-dione and a pyrrolidine-2,5-dione moiety, respectively. A plausible biosynthetic pathway for 1-3 is proposed. All diterpenoids were evaluated for their cytotoxic activity against non-small-cell lung cancer lines (A549 and H460) and gastric cancer lines (HGC27 and AGS). Among them, 2 and 14 showed moderate cytotoxicity against four cell lines.

Key genes and regulatory networks for diabetic retinopathy based on hypoxia-related genes: a bioinformatics analysis.

AIM: To prevent neovascularization in diabetic retinopathy (DR) patients and partially control disease progression. METHODS: Hypoxia-related differentially expressed genes (DEGs) were identified from the GSE60436 and GSE102485 datasets, followed by gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Potential candidate drugs were screened using the CMap database. Subsequently, a protein-protein interaction (PPI) network was constructed to identify hypoxia-related hub genes. A nomogram was generated using the rms R package, and the correlation of hub genes was analyzed using the Hmisc R package. The clinical significance of hub genes was validated by comparing their expression levels between disease and normal groups and constructing receiver operating characteristic curve (ROC) curves. Finally, a hypoxia-related miRNA-transcription factor (TF)-Hub gene network was constructed using the NetworkAnalyst online tool. RESULTS: Totally 48 hypoxia-related DEGs and screened 10 potential candidate drugs with interaction relationships to upregulated hypoxia-related genes were identified, such as ruxolitinib, meprylcaine, and deferiprone. In addition, 8 hub genes were also identified: glycogen phosphorylase muscle associated (PYGM), glyceraldehyde-3-phosphate dehydrogenase spermatogenic (GAPDHS), enolase 3 (ENO3), aldolase fructose-bisphosphate C (ALDOC), phosphoglucomutase 2 (PGM2), enolase 2 (ENO2), phosphoglycerate mutase 2 (PGAM2), and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3). Based on hub gene predictions, the miRNA-TF-Hub gene network revealed complex interactions between 163 miRNAs, 77 TFs, and hub genes. The results of ROC showed that the except for GAPDHS, the area under curve (AUC) values of the other 7 hub genes were greater than 0.758, indicating their favorable diagnostic performance. CONCLUSION: PYGM, GAPDHS, ENO3, ALDOC, PGM2, ENO2, PGAM2, and PFKFB3 are hub genes in DR, and hypoxia-related hub genes exhibited favorable diagnostic performance.

Anopheles gambiae lacking AgTRIO probe inefficiently on a mammalian host.

Malaria is initiated as Plasmodium sporozoites are injected into the dermis when an infected mosquito probes on a vertebrate host for a blood meal. Factors in the mosquito saliva, such as AgTRIO, can alter the ability of Anopheles gambiae to transmit Plasmodium. We therefore used CRISPR-Cas9-mediated genome editing to generate AgTRIO knockout (KO) A. gambiae and examined the ability of these mosquitoes to probe on a vertebrate host. AgTRIO KO mosquitoes showed a diminished host probing capacity and required repetitive probing to locate a blood resource to complete a blood meal. This increased probing resulted in enhanced Plasmodium transmission to the vertebrate host. Our data demonstrate the importance of the A. gambiae saliva protein AgTRIO in probing and its influence on the ability of mosquitoes to transmit malaria.

Unsupervised Part Discovery via Dual Representation Alignment.

Object parts serve as crucial intermediate representations in various downstream tasks, but part-level representation learning still has not received as much attention as other vision tasks. Previous research has established that Vision Transformer can learn instance-level attention without labels, extracting high-quality instance-level representations for boosting downstream tasks. In this paper, we achieve unsupervised part-specific attention learning using a novel paradigm and further employ the part representations to improve part discovery performance. Specifically, paired images are generated from the same image with different geometric transformations, and multiple part representations are extracted from these paired images using a novel module, named PartFormer. These part representations from the paired images are then exchanged to improve geometric transformation invariance. Subsequently, the part representations are aligned with the feature map extracted by a feature map encoder, achieving high similarity with the pixel representations of the corresponding part regions and low similarity in irrelevant regions. Finally, the geometric and semantic constraints are applied to the part representations through the intermediate results in alignment for part-specific attention learning, encouraging the PartFormer to focus locally and the part representations to explicitly include the information of the corresponding parts. Moreover, the aligned part representations can further serve as a series of reliable detectors in the testing phase, predicting pixel masks for part discovery. Extensive experiments are carried out on four widely used datasets, and our results demonstrate that the proposed method achieves competitive performance and robustness due to its part-specific attention. The code will be released upon paper acceptance.