Personalized Prediction of Long-Term Renal Function Prognosis Following Nephrectomy Using Interpretable Machine Learning Algorithms: Case-Control Study.

BACKGROUND: Acute kidney injury (AKI) is a common adverse outcome following nephrectomy. The progression from AKI to acute kidney disease (AKD) and subsequently to chronic kidney disease (CKD) remains a concern; yet, the predictive mechanisms for these transitions are not fully understood. Interpretable machine learning (ML) models offer insights into how clinical features influence long-term renal function outcomes after nephrectomy, providing a more precise framework for identifying patients at risk and supporting improved clinical decision-making processes. OBJECTIVE: This study aimed to (1) evaluate postnephrectomy rates of AKI, AKD, and CKD, analyzing long-term renal outcomes along different trajectories; (2) interpret AKD and CKD models using Shapley Additive Explanations values and Local Interpretable Model-Agnostic Explanations algorithm; and (3) develop a web-based tool for estimating AKD or CKD risk after nephrectomy. METHODS: We conducted a retrospective cohort study involving patients who underwent nephrectomy between July 2012 and June 2019. Patient data were randomly split into training, validation, and test sets, maintaining a ratio of 76.5:8.5:15. Eight ML algorithms were used to construct predictive models for postoperative AKD and CKD. The performance of the best-performing models was assessed using various metrics. We used various Shapley Additive Explanations plots and Local Interpretable Model-Agnostic Explanations bar plots to interpret the model and generated directed acyclic graphs to explore the potential causal relationships between features. Additionally, we developed a web-based prediction tool using the top 10 features for AKD prediction and the top 5 features for CKD prediction. RESULTS: The study cohort comprised 1559 patients. Incidence rates for AKI, AKD, and CKD were 21.7% (n=330), 15.3% (n=238), and 10.6% (n=165), respectively. Among the evaluated ML models, the Light Gradient-Boosting Machine (LightGBM) model demonstrated superior performance, with an area under the receiver operating characteristic curve of 0.97 for AKD prediction and 0.96 for CKD prediction. Performance metrics and plots highlighted the model's competence in discrimination, calibration, and clinical applicability. Operative duration, hemoglobin, blood loss, urine protein, and hematocrit were identified as the top 5 features associated with predicted AKD. Baseline estimated glomerular filtration rate, pathology, trajectories of renal function, age, and total bilirubin were the top 5 features associated with predicted CKD. Additionally, we developed a web application using the LightGBM model to estimate AKD and CKD risks. CONCLUSIONS: An interpretable ML model effectively elucidated its decision-making process in identifying patients at risk of AKD and CKD following nephrectomy by enumerating critical features. The web-based calculator, found on the LightGBM model, can assist in formulating more personalized and evidence-based clinical strategies.

HBsAg and TLR7/8 dual-targeting antibody-drug conjugates induce sustained anti-HBV activity in AAV/HBV mice: a preliminary study.

Hepatitis B virus (HBV) infection is a significant global health concern due to elevated immunosuppressive viral antigen levels, the host immune system's inability to manage HBV, and the liver's immunosuppressive conditions. While immunotherapies utilizing broadly reactive HBV neutralizing antibodies present potential due to their antiviral capabilities and Fc-dependent vaccinal effects, they necessitate prolonged and frequent dosing to achieve optimal therapeutic outcomes. Toll-like receptor 7/8 (TLR7/8) agonists have been demonstrated promise for the cure of chronic hepatitis B, but their systemic use often leads to intense side effects. In this study, we introduced immune-stimulating antibody conjugates which consist of TLR7/8 agonists 1-[[4-(aminomethyl)phenyl]methyl]-2-butyl-imidazo[4,5-c]quinolin-4-amine (IMDQ) linked to an anti-hepatitis B surface antigen (HBsAg) antibody 129G1, and designated as 129G1-IMDQ. Our preliminary study highlights that 129G1-IMDQ can prompt robust and sustained anti-HBsAg specific reactions with short-term administration. This underscores the conjugate's potential as an effective strategy for HBsAg clearance and seroconversion, offering a fresh perspective for a practical therapeutic approach in the functional cure of CHB. Highlights: HBV-neutralizing antibody 129G1 was linked with a TLR7/8 agonist small molecule compound IMDQ.Treatment with 129G1-IMDQ has shown significant promise in lowering HBsAg levels in AAV/HBV mice.129G1-IMDQ were eliciting a strong and lasting anti-HBsAg immune response after short-term treatment in AAV/HBV mice.

Formononetin Alleviates Ischemic Acute Kidney Injury by Regulating Macrophage Polarization through KLF6/STAT3 Pathway.

Recent research has indicated that formononetin demonstrates a potent anti-inflammatory effect in various diseases. However, its impact on sterile inflammation kidney injury, specifically acute kidney injury (AKI), remains unclear. In this study, we utilized an ischemia/reperfusion-induced AKI (IRI-AKI) mouse model and bone marrow-derived macrophages (BMDMs) to investigate the effects of formononetin on sterile inflammation of AKI and to explore the underlying mechanism. The administration of formononetin significantly preserved kidney function from injury, as evidenced by lower serum creatinine and blood urea nitrogen levels compared to IRI-AKI mice without treatment. This was further confirmed by less pathological changes in renal tubules and low expression of tubular injury markers such as KIM-1 and NGAL in the formononetin-treated IRI-AKI group. Furthermore, formononetin effectively suppressed the expression of pro-inflammatory cytokines (MCP-1, TNF-α, and IL-1ß) and macrophage infiltration into the kidneys of AKI mice. In vitro studies showed that formononetin led to less macrophage polarization towards a pro-inflammatory phenotype in BMDMs stimulated by LPS and IFN-[Formula: see text]. The mechanism involved the KLF6 and p-STAT3 pathway, as overexpression of KLF6 restored pro-inflammatory cytokine levels and pro-inflammatory polarization. Our findings demonstrate that formononetin can significantly improve renal function and reduce inflammation in IRI-AKI, which may be attributed to the inhibition of KLF6/STAT3-mediated macrophage pro-inflammatory polarization. This discovery presents a new promising therapeutic option for the treatment of IRI-AKI.

Personalized prediction of mortality in patients with acute ischemic stroke using explainable artificial intelligence.

BACKGROUND: Research into the acute kidney disease (AKD) after acute ischemic stroke (AIS) is rare, and how clinical features influence its prognosis remain unknown. We aim to employ interpretable machine learning (ML) models to study AIS and clarify its decision-making process in identifying the risk of mortality. METHODS: We conducted a retrospective cohort study involving AIS patients from January 2020 to June 2021. Patient data were randomly divided into training and test sets. Eight ML algorithms were employed to construct predictive models for mortality. The performance of the best model was evaluated using various metrics. Furthermore, we created an artificial intelligence (AI)-driven web application that leveraged the top ten most crucial features for mortality prediction. RESULTS: The study cohort consisted of 1633 AIS patients, among whom 257 (15.74%) developed subacute AKD, 173 (10.59%) experienced AKI recovery, and 65 (3.98%) met criteria for both AKI and AKD. The mortality rate stood at 4.84%. The LightGBM model displayed superior performance, boasting an AUROC of 0.96 for mortality prediction. The top five features linked to mortality were ACEI/ARE, renal function trajectories, neutrophil count, diuretics, and serum creatinine. Moreover, we designed a web application using the LightGBM model to estimate mortality risk. CONCLUSIONS: Complete renal function trajectories, including AKI and AKD, are vital for fitting mortality in AIS patients. An interpretable ML model effectively clarified its decision-making process for identifying AIS patients at risk of mortality. The AI-driven web application has the potential to contribute to the development of personalized early mortality prevention.

Facile synthesis of MoS2@red phosphorus heterojunction for synergistically photodynamic and photothermal therapy of renal cell carcinoma.

The therapy of the clear cell renal cell carcinoma (ccRCC) is crucial for the human healthcare due to its easy metastasis and recurrence, as well as resistance to radiotherapy and chemotherapy. In this work, we propose the synthesis of MoS2@red phosphorus (MoS2@RP) heterojunction to induce synergistic photodynamic and photothermal therapy (PDT/PTT) of ccRCC. The MoS2@RP heterojunction exhibits enhanced spectra absorption in the NIR range and produce local heat-increasing under the NIR laser irradiation compared with pure MoS2 and RP. The high photocatalytic activity of the MoS2@RP heterojunction contributes to effective transferring of the photo-excited electrons from the RP to MoS2, which promotes the production of various types of radical oxygen species (ROS) to kill the ccRCC cells. After the NIR irradiation, the MoS2@RP can effectively induce the apoptosis in the ccRCC cells through localized hyperthermia and the generation of ROS, while exhibiting low cytotoxicity towards normal kidney cells. In comparison to MoS2, the MoS2@RP heterojunction shows an approximate increase of 22 % in the lethality rate of the ccRCC cells and no significant change in toxicity towards normal cells. Furthermore, the PDT/PTT treatment using the MoS2@RP heterojunction effectively eradicates a substantial number of deep-tissue ccRCC cells in vivo without causing significant damage to major organs. This study presents promising effect of the MoS2@RP heterojunction-based photo-responsive therapy for effective ccRCC treatment.

Investigating a Machine Learning Approach to Predicting White Pixel Defects in Wafers-A Case Study of Wafer Fabrication Plant F.

CMOS image sensor (CIS) semiconductor products are integral to mobile phones and photographic devices, necessitating ongoing enhancements in efficiency and quality for superior photographic outcomes. The presence of white pixels serves as a crucial metric for assessing CIS product performance, primarily arising from metal impurity contamination during the wafer production process or from defects introduced by the grinding blade process. While immediately addressing metal impurity contamination during production presents challenges, refining the handling of defects attributed to grinding blade processing can notably mitigate white pixel issues in CIS products. This study zeroes in on silicon wafer manufacturers in Taiwan, analyzing white pixel defects reported by customers and leveraging machine learning to pinpoint and predict key factors leading to white pixel defects from grinding blade operations. Such pioneering practical studies are rare. The findings reveal that the classification and regression tree (CART) and random forest (RF) models deliver the most accurate predictions (95.18%) of white pixel defects caused by grinding blade operations in a default parameter setting. The analysis further elucidates critical factors like grinding load and torque, vital for the genesis of white pixel defects. The insights garnered from this study aim to arm operators with proactive measures to diminish the potential for customer complaints.

Cone-wedge anchored surgical templates for stackable metal guide: a novel technique.

OBJECTIVE: To address the instability in implant surgical guides, this technique proposes an alternative anchoring mechanism in the stackable metal surgical guides utilizing cone-wedge anchors for improved stability. METHODS: Postoperative implant position superimposed onto the preoperatively planned design using Mimics Medical 21.0 and Materialise Magics 24.0 to assess 3D coronal implant deviation, 3D apical implant deviation, and implant angular deviation. RESULTS: Postoperative cone-beam computed tomography (CBCT) revealed a high level of precision in the implant placement, with an average 0.97 mm deviation at implant coronal region, 1.56 mm at implant apexes, and 2.95° angular deviation. CONCLUSION: This technique introduces a novel cone-wedge anchoring mechanism to enhance the stability of stackable metal surgical guide templates, addressing inherent instability issues. The utilization of this approach significantly improves the accuracy of implant placement procedures.

Hyperbaric oxygen therapy enhances osteointegration of reimplanted cranial flap by regulating osteogenesis-angiogenesis coupling.

Craniectomy is a lifesaving procedure to alleviate dangerously high intracranial pressure by removing a bone flap from the calvarium. However, the osteointegration of reimplanted bone flap with the existing bone tissue is still a clinical challenge. Hyperbaric oxygen (HBO) therapy has shown efficacy in promoting bone repair and could be a promising treatment for accelerating postoperative recovery. However, the specific cell types that are responsive to HBO treatment are not well understood. In this study, we created a murine model of craniectomy, with reimplantation of the cranial flap after 1 week. The effects of HBO treatment on bone formation and blood vessel formation around reimplanted bone were examined by micro-computed tomography, histological staining, and immunofluorescence staining. Single-cell RNA sequencing (scRNAseq) was utilized to identify key cell subtypes and signaling pathways after HBO treatment. We found that HBO treatment increased bone volume around reimplanted cranial flaps. HBO also increased the volume of Osterix-expressing cells and type H vessels. scRNAseq data showed more mature osteoblasts and endothelial cells, with higher expressions of adhesion and migration-related genes after HBO treatment. Cell-cell interaction analysis revealed a higher expression level of genes between mature osteoblasts and endothelial cells from the angiopoietin 2-integrin α5ß1 pathway. Taken together, HBO therapy promotes the healing process of craniectomy by regulating the crosstalk between vascular endothelial cells and osteogenic cells. These findings provide evidence in a preclinical model that HBO therapy enhances osteointegration by regulating angiogenesis-osteogenesis coupling, providing a scientific basis for utilizing HBO therapy for accelerating postoperative recovery after craniectomy.

The effects of pterygomaxillary disjunction in surgically assisted rapid maxillary expansion: A systematic review and meta-analysis.

OBJECTIVE: This study aims to assess the expansive effects of pterygomaxillary disjunction (PMD) in surgically assisted rapid maxillary expansion (SARME) surgery using a meta-analysis approach. MATERIALS AND METHODS: The study conducted a comprehensive literature search across five databases: PubMed, Scopus, Medline, Embase, and Cochrane, adhering to the PRISMA 2020 guidelines. Dental alterations were assessed using either cone-beam computed tomography (CBCT) or dental casts, while skeletal changes were exclusively measured from CBCT scans. We analysed the dentoskeletal changes between PMD +/- groups and conducted a within-group comparison. The primary focus of the results was on the mean differences observed in pre- and post-operative measurements. RESULTS: Dental expansion was larger in the PMD+ group but not statistically significant. Skeletal expansion showed a significantly larger expansion in the posterior region in the PMD+ group (P = .033). Without PMD, anterior palatal expansion was significantly larger (P = .03), and the buccal tipping of posterior teeth was also significantly larger (P = .011) to achieve acceptable dental expansion outcomes. CONCLUSIONS: Both PMD +/- groups of SARME surgery can achieve satisfactory dental expansion outcomes. However, bone expansion and tooth inclination are also important factors that influence orthodontic treatment and post-expansion stability. By reducing the bony resistance with PMD, larger posterior palatal expansion and more parallel bony expansion are observed. In contrast, without PMD, there is smaller palatal expansion and greater tooth inclination in the posterior region. This could potentially lead to compromised periodontal conditions following expansion.

Vaporization phosphorization-mediated synthesis of phosphorus-doped TiO2 nanocomposites for combined photodynamic and photothermal therapy of renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is a disease with high incidence and poor prognosis. The conventional treatment involves radiotherapy and chemotherapy, but chemotherapeutic agents are often associated with side effects, i.e., cytotoxicity to nontumor cells. Therefore, there is an urgent need for the development of novel therapeutic strategies for ccRCC. We synthesized spherical P/TiO2 nanoparticles (P/TiO2 NPs) by vaporization phosphorization (VP). X-ray photoelectron spectroscopy (XPS) and ultraviolet-visible diffuse reflectance spectroscopy (UV-Vis DRS) analyses confirmed that the anatase TiO2 surface was successfully doped with phosphorus and produced a large number of oxygen vacancies (OV). Serving as a photosensitizer, P/TiO2 NPs not only extended the photoresponse range to the near-infrared II region (NIR II) but also introduced a donor energy level lower than the TiO2 conduction band, narrowing the band gap, which could facilitate the migration of photogenerated charges and trigger the synergistic treatment of photodynamic therapy (PDT) and photothermal therapy (PTT). During NIR irradiation in vitro, the P/TiO2 NPs generated local heat and various oxygen radicals, including 1O2, ˙O2-, H2O2, and ˙OH, which damaged the ccRCC cells. In vivo, administration of the P/TiO2 NPs + NIR reduced the tumor volume by 80%, and had the potential to inhibit tumor metastasis by suppressing intratumor neoangiogenesis. The P/TiO2 NPs showed superior safety and efficacy relative to the conventional chemotherapeutic agent used in ccRCC treatment. This study introduced an innovative paradigm for renal cancer treatment, highlighting the potential of P/TiO2 NPs as safe and effective nanomaterials and presenting a compelling new option for clinical applications in anticancer therapy.

Binocular Visual Measurement Method Based on Feature Matching.

To address the issues of low measurement accuracy and unstable results when using binocular cameras to detect objects with sparse surface textures, weak surface textures, occluded surfaces, low-contrast surfaces, and surfaces with intense lighting variations, a three-dimensional measurement method based on an improved feature matching algorithm is proposed. Initially, features are extracted from the left and right images obtained by the binocular camera. The extracted feature points serve as seed points, and a one-dimensional search space is established accurately based on the disparity continuity and epipolar constraints. The optimal search range and seed point quantity are obtained using the particle swarm optimization algorithm. The zero-mean normalized cross-correlation coefficient is employed as a similarity measure function for region growing. Subsequently, the left and right images are matched based on the grayscale information of the feature regions, and seed point matching is performed within each matching region. Finally, the obtained matching pairs are used to calculate the three-dimensional information of the target object using the triangulation formula. The proposed algorithm significantly enhances matching accuracy while reducing algorithm complexity. Experimental results on the Middlebury dataset show an average relative error of 0.75% and an average measurement time of 0.82 s. The error matching rate of the proposed image matching algorithm is 2.02%, and the PSNR is 34 dB. The algorithm improves the measurement accuracy for objects with sparse or weak textures, demonstrating robustness against brightness variations and noise interference.

Establishment and verification of a nomogram that predicts the risk for coronary slow flow.

Background: Coronary slow flow (CSF) has gained significance as a chronic coronary artery disease, but few studies have integrated both biological and anatomical factors for CSF assessment. This study aimed to develop and validate a simple-to-use nomogram for predicting CSF risk by combining biological and anatomical factors. Methods: In this retrospective case-control study, 1042 patients (614 CSF cases and 428 controls) were randomly assigned to the development and validation cohorts at a 7:3 ratio. Potential predictive factors were identified using least absolute shrinkage and selection operator regression and subsequently utilized in multivariate logistic regression to construct the nomogram. Validation of the nomogram was assessed by discrimination and calibration. Results: N-terminal pro brain natriuretic peptide, high density lipoprotein cholesterol, hemoglobin, left anterior descending artery diameter, left circumflex artery diameter, and right coronary artery diameter were independent predictors of CSF. The model displayed high discrimination in the development and validation cohorts (C-index 0.771, 95% CI: 0.737-0.805 and 0.805, 95% CI: 0.757-0.853, respectively). The calibration curves for both cohorts showed close alignment between predicted and actual risk estimates, demonstrating improved model calibration. Decision curve analysis suggested high clinical utility for the predictive nomogram. Conclusion: The constructed nomogram accurately and individually predicts the risk of CSF for patients with suspected CSF and may be considered for use in clinical care.

Construction of an immune predictive model and identification of TRIP6 as a prognostic marker and therapeutic target of CRC by integration of single-cell and bulk RNA-seq data.

BACKGROUND: Investigations elucidating the complex immunological mechanisms involved in colorectal cancer (CRC) and accurately predicting patient outcomes via bulk RNA-Seq analysis have been notably limited. This study aimed to identify the immune status of CRC patients, construct a prognostic model, and identify prognostic signatures via bulk RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq). METHODS: The scRNA-seq data of CRC were downloaded from Gene Expression Omnibus (GEO). The UCSC Xena database was used to obtain bulk RNA-seq data. Differentially expressed gene (DEG), functional enrichment, and random forest analyses were conducted in order to identify core genes associated with colorectal cancer (CRC) that were relevant to prognosis. A molecular immune prediction model was developed using logistic regression after screening features using the least absolute shrinkage and selection operator (LASSO). The differences in immune cell infiltration, mutation, chemotherapeutic drug sensitivity, cellular senescence, and communication between patients who were at high and low risk of CRC according to the predictive model were investigated. The prognostic genes that were closely associated with CRC were identified by random survival forest (RSF) analysis. The expression levels and clinical significance of the hub genes were analyzed in vitro. The LoVo cell line was employed to ascertain the biological role of thyroid hormone receptor-interacting protein 6 (TRIP6). RESULTS: A total of seven main cell subtypes were identified by scRNA-seq analysis. A molecular immune predictive model was constructed based on the risk scores. The risk score was significantly associated with OS, stage, mutation burden, immune cell infiltration, response to immunotherapy, key pathways, and cell-cell communication. The functions of the six hub genes were determined and further utilized to establish a regulatory network. Our findings unequivocally confirmed that TRIP6 upregulation was verified in the CRC samples. After knocking down TRIP6, cell proliferation, migration, and invasion of LoVo cells were inhibited, and apoptosis was promoted. CONCLUSIONS: The molecular predictive model reliably distinguished the immune status of CRC patients. We further revealed that TRIP6 may act as an oncogene in CRC, making it a promising candidate for targeted therapy and as a prognostic marker for CRC.

Clinical characteristics of obese, fixed airway obstruction, exacerbation-prone phenotype and comorbidities among severe asthma patients: a single-center study.

BACKGROUND: Severe asthma places a large burden on patients and society. The characteristics of patients with severe asthma in the Chinese population remain unclear. METHODS: A retrospective review was conducted in patients with severe asthma. Demographic and clinical data were collected. Patients were grouped according to phenotypes in terms of exacerbations, body mass index (BMI) and fixed airway obstruction (FAO) status, and the characteristics of different groups were compared. Comorbidities, factors that influence asthma phenotypes, were also analyzed in the study. RESULTS: A total of 228 patients with severe asthma were included in our study. They were more likely to be overweight or obese. A total of 41.7% of the patients received GINA step 5 therapy, and 43.4% had a history of receiving regular or intermittent oral corticosteroids (OCS). Severe asthmatic patients with comorbidities were prone to have more asthma symptoms and decreased quality of life than patients without comorbidities. Patients with exacerbations were characterized by longer duration of asthma, poorer lung function, and worse asthma control. Overweight or obese patients tended to have more asthma symptoms, poorer lung function and more asthma-related comorbidities. Compared to patients without FAO, those in the FAO group were older, with longer duration of asthma and more exacerbations. CONCLUSION: The existence of comorbidities in patients with severe asthma could result in more asthma symptoms and decreased quality of life. Patients with exacerbations or with overweight or obese phenotypes were characterized by poorer lung function and worse asthma control. Patients with FAO phenotype tended to have more exacerbations.

Major Adverse Cardiovascular Events and Prognosis in Patients With Coronary Slow Flow.

This study aimed to investigate its clinical implications, risk factors, prognosis, and overall long-term outcomes. Demographic profiles, various clinical characteristics, and clinical outcomes were compared between 614 patients with coronary slow flow (CSF) and 428 patients with normal coronary artery. The incidence of CSF was found to be 2.65%. Significant differences were observed between patients with CSF and control subjects in terms of sex, chest tightness, hyperlipidemia, smoking history, alcohol consumption, age, height, weight, body mass index, diastolic blood pressure, heart rate, and body surface area (P < 0.05). CSF (hazard ratio: 1.531; 95% confidence interval: 1.064-2.202; p = 0.022) proved to be independent prognostic predictors of major adverse cardiovascular events (MACEs). Kaplan-Meier survival evaluations for MACEs presented a worser outcome for patients with CSF. Patients with CSF are at high risk for cardiovascular events and experience generally poor clinical outcomes.

Rational design of a cross-type HPV vaccine through immunodominance shift guided by a cross-neutralizing antibody.

In vaccine development, broadly or cross-type neutralizing antibodies (bnAbs or cnAbs) are frequently targeted to enhance protection. Utilizing immunodominant antibodies could help fine-tune vaccine immunogenicity and augment the precision of immunization strategies. However, the methodologies to capitalize on the attributes of bnAbs in vaccine design have not been clearly elucidated. In this study, we discovered a cross-type neutralizing monoclonal antibody, 13H5, against human papillomavirus 6 (HPV6) and HPV11. This nAb exhibited a marked preference for HPV6, demonstrating superior binding activity to virus-like particles (VLPs) and significantly higher prevalence in anti-HPV6 human serum as compared to HPV11 antiserum (90% vs. 31%). Through co-crystal structural analysis of the HPV6 L1 pentamer:13H5 complex, we delineated the epitope as spanning four segments of amino acids (Phe42-Ala47, Gly172-Asp173, Glu255-Val275, and Val337-Tyr351) on the L1 surface loops. Further interaction analysis and site-directed mutagenesis revealed that the Ser341 residue in the HPV6 HI loop plays a critical role in the interaction between 13H5 and L1. Substituting Ser341 with alanine, which is the residue type present in HPV11 L1, almost completely abolished binding activity to 13H5. By swapping amino acids in the HPV11 HI loop with corresponding residues in HPV6 L1 (Ser341, Thr338, and Thr339), we engineered chimeric HPV11-6HI VLPs. Remarkably, the chimeric HPV11-6HI VLPs shifted the high immunodominance of 13H5 from HPV6 to the engineered VLPs and yielded comparable neutralization titers for both HPV6 and HPV11 in mice and non-human primates. This approach paves the way for the design of broadly protective vaccines from antibodies within the main immunization reservoir.

Allyl Isothiocyanate Suppresses the Proliferation in Oral Squamous Cell Carcinoma via Mediating the KDM8/CCNA1 Axis.

The dysregulated expression of cyclin genes can lead to the uncontrolled proliferation of cancer cells. Histone demethylase Jumonji-C domain-containing protein 5 (KDM8, JMJD5) and cyclin A1 (CCNA1) are pivotal in cell cycle progression. A promising candidate for augmenting cancer treatment is Allyl isothiocyanate (AITC), a natural dietary chemotherapeutic and epigenetic modulator. This study aimed to investigate AITC's impact on the KDM8/CCNA1 axis to elucidate its role in oral squamous cell carcinoma (OSCC) tumorigenesis. The expression of KDM8 and CCNA1 was assessed using a tissue microarray (TMA) immunohistochemistry (IHC) assay. In vitro experiments with OSCC cell lines and in vivo experiments with patient-derived tumor xenograft (PDTX) and SAS subcutaneous xenograft tumor models were conducted to explore AITC's effects on their expression and cell proliferation. The results showed elevated KDM8 and CCNA1 levels in the OSCC patient samples. AITC exhibited inhibitory effects on OSCC tumor growth in vitro and in vivo. Additionally, AITC downregulated KDM8 and CCNA1 expression while inducing histone H3K36me2 expression in oral cancer cells. These findings underscore AITC's remarkable anticancer properties against oral cancer, highlighting its potential as a therapeutic option for oral cancer treatment by disrupting the cell cycle by targeting the KDM8/CCNA1 axis.

Bone disease imaging through the near-infrared-II window.

Skeletal disorders are commonly diagnosed by X-ray imaging, but the radiation limits its use. Optical imaging through the near-infrared-II window (NIR-II, 1000-1700 nm) can penetrate deep tissues without radiation risk, but the targeting of contrast agent is non-specific. Here, we report that lanthanide-doped nanocrystals can passively target the bone marrow, which can be effective for over two months. We therefore develop the high-resolution NIR-II imaging method for bone disease diagnosis, including the 3D bone imaging instrumentation to show the intravital bone morphology. We demonstrate the monitoring of 1 mm bone defects with spatial resolution comparable to the X-ray imaging result. Moreover, NIR-II imaging can reveal the early onset inflammation as the synovitis in the early stage of rheumatoid arthritis, comparable to micro computed tomography (µCT) in diagnosis of osteoarthritis, including the symptoms of osteophyte and hyperostosis in the knee joint.

Hospitalized patients received furosemide undergoing acute kidney injury: the risk and prediction tool.

PURPOSE: Furosemide, a frequently prescribed diuretic for managing congestive heart failure and edema, remains a topic of debate regarding its potential risk of inducing acute kidney injury (AKI) in patients. Consequently, this study aims to examine the occurrence of hospital-acquired AKI (HA-AKI) in hospitalized patients who are administered furosemide and to investigate potential risk factors associated with this outcome. METHODS: This study encompassed a cohort of 22374 hospitalized patients who either received furosemide treatment or not from June 1, 2012, to December 31, 2017. Propensity score matching was employed to establish comparability between the two groups regarding covariates. Subsequently, a nomogram was constructed to predict the probability of AKI occurrence among patients who underwent furosemide treatment. RESULTS: The regression analysis identified the single-day total dose of furosemide as the most significant factor for AKI, followed by ICU administration, estimated glomerular filtration rate, antibiotic, statin, NSAIDs, ß-blockers, proton pump inhibitor, chronic kidney disease, and 7 other indicators. Subgroup analysis revealed a synergistic effect of furosemide with surgical operation, previous treatment with ß-blockers, ACEI/ARB and antibiotics, leading to an increased risk of AKI when used in combination. Subsequently, a visually represented prognostic nomogram was developed to predict AKI occurrence in furosemide users. The predictive accuracy of the nomogram was assessed through calibration analyses, demonstrating an excellent agreement between the nomogram predictions and the actual likelihood of AKI, with a probability of 77.40%. CONCLUSIONS: Careful consideration of factors such as dosage, concurrent medication use, and renal function of the patient is necessary for clinical practice when using furosemide. Our practical prognostic model for HA-AKI associated with furosemide use can be utilized to assist clinicians in making informed decisions about patient care and treatment.