Pairpot: a database with real-time lasso-based analysis tailored for paired single-cell and spatial transcriptomics.

Paired single-cell and spatially resolved transcriptomics (SRT) data supplement each other, providing in-depth insights into biological processes and disease mechanisms. Previous SRT databases have limitations in curating sufficient single-cell and SRT pairs (SC-SP pairs) and providing real-time heuristic analysis, which hinder the effort to uncover potential biological insights. Here, we developed Pairpot (http://pairpot.bioxai.cn), a database tailored for paired single-cell and SRT data with real-time heuristic analysis. Pairpot curates 99 high-quality pairs including 1,425,656 spots from 299 datasets, and creates the association networks. It constructs the curated pairs by integrating multiple slices and establishing potential associations between single-cell and SRT data. On this basis, Pairpot adopts semi-supervised learning that enables real-time heuristic analysis for SC-SP pairs where Lasso-View refines the user-selected SRT domains within milliseconds, Pair-View infers cell proportions of spots based on user-selected cell types in real-time and Layer-View displays SRT slices using a 3D hierarchical layout. Experiments demonstrated Pairpot's efficiency in identifying heterogeneous domains and cell proportions.

Postoperative Injection of a Triptolide-Preloaded Hydrogel Prevents the Recurrence of Glioblastoma by Dual-Pathway Activation of Ferroptosis.

Glioblastoma (GBM) recurrence leads to high mortality, which remains a major concern in clinical therapy. Herein, an injectable triptolide (TP)-preloaded hydrogel (TP@DNH) accompanied by a postoperative injection strategy is developed to prevent the recurrence of GBM. With a potential inhibitor of the NRF2/SLC7A11/GPX4 axis, it is demonstrated that TP can deactivate glutathione peroxidase 4 (GPX4) from the source of glutathione (GSH) biosynthesis, thereby activating ferroptosis in GBM cells by blocking the neutralization of intracellular lipid peroxide (LPO). Based on acid-sensitive Fe3+/tannic acid (TA) metal-phenolic networks (MPNs), the TP@DNH hydrogel can induce the effective generation of reactive oxygen species (ROS) through Fe3+/TA-mediated Fenton reaction and achieve controllable release of TP in resected GBM cavity. Due to ROS generation and GPX4 deactivation, postoperative injection of TP@DNH can achieve high-level ferroptosis through dual-pathway LPO accumulation, remarkably suppressing the growth of recurrent GBM and prolonging the overall survival in orthotopic GBM relapse mouse model. This work provides an alternative paradigm for regulating ferroptosis in the postoperative treatment of GBM.

Analysis of low-density lipoprotein receptor gene mutations in a family with familial hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is a common monogenic autosomal dominant disorder, primarily mainly caused by pathogenic mutations in the low-density lipoprotein receptor (LDLR) gene. Through phenotypic-genetic linkage analysis, two LDLR pathogenic mutations were identified in FH families: c.G1027A (p.Gly343Ser) and c.G1879A (p.Ala627Thr). MATERIALS AND METHODS: Whole exome sequencing was conducted on the proband with familial hypercholesterolemia to identify the target gene and screen for potential pathogenic mutations. The suspicious responsible mutation sites in 14 family members were analyzed using Sanger sequencing to assess genotype-phenotype correlations. Mutant and wild type plasmids were constructed and transfected into HEK293T cells to evaluate LDLR mRNA and protein expression. In parallel, bioinformatics tools were employed to predict structural and functional changes in the mutant LDLR. RESULTS: Immunofluorescence analysis revealed no significant difference in the intracellular localization of the p.Gly343Ser mutation, whereas protein expression of the p.Ala627Thr mutation was decreased and predominantly localized in the cytoplasm. Western blotting has showed that protein expression levels of the mutant variants were markedly declined in both cell lysates and supernatants. Enzyme linked immunosorbent assay has demonstrated that LDLR protein levels in the supernatant of cell culture medium was not significant different from those of the wild-type group. However, LDLR protein levels in the cell lysate of both the Gly343Ser and Ala627Thr variants groups were significantly lower than those in the wild-type group. Bioinformatic predictions further suggested that these mutations may affect post-translational modifications of the protein, providing additional insight into the mechanisms underlying the observed reduction in protein expression. CONCLUSIONS: In this study, we identified two heterozygous pathogenic variants in the LDLR gene, c.G1027A (p.Gly343Ser) and c.G1879A (p.Ala627Thr), in a family with familial hypercholesterolemia. We also conducted preliminary investigations into the mechanisms by which these mutations contribute to disease pathology.

Graphene-Doped Piezoelectric Transducers by Kriging Optimal Model for Detecting Various Types of Laryngeal Movements.

This study fabricated piezoelectric fibers of polyvinylidene fluoride (PVDF) with graphene using near-field electrospinning (NFES) technology. A uniform experimental design table U*774 was applied, considering weight percentage (1-13 wt%), the distance between needle and disk collector (2.1-3.9 mm), and applied voltage (14.5-17.5 kV). We optimized the parameters using electrical property measurements and the Kriging response surface method. Adding 13 wt% graphene significantly improved electrical conductivity, increasing from 17.7 µS/cm for pure PVDF to 187.5 µS/cm. The fiber diameter decreased from 21.4 µm in PVDF/1% graphene to 9.1 µm in PVDF/13% graphene. Adding 5 wt% graphene increased the ß-phase content by 6.9%, reaching 65.4% compared to pure PVDF fibers. Material characteristics were investigated using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction analysis (XRD), contact angle measurements, and tensile testing. Optimal parameters included 3.47 wt% graphene, yielding 15.82 mV voltage at 5 Hz and 5 N force (2.04 times pure PVDF). Force testing showed a sensitivity (S) of 7.67 log(mV/N). Fibers were attached to electrodes for piezoelectric sensor applications. The results affirmed enhanced electrical conductivity, piezoelectric performance, and mechanical strength. The optimized piezoelectric sensor could be applied to measure physiological signals, such as attaching it to the throat under different conditions to measure the output voltage. The force-to-voltage conversion facilitated subsequent analysis.

A Novel ANG-BSA/BCNU/ICG MNPs Integrated for Targeting Therapy of Glioblastoma.

PURPOSE: Develop an albumin nanoparticle-based nanoprobe for targeted glioblastoma (GBM) diagnosis and treatment, utilizing Angopep-2 for low-density lipoprotein receptor-related protein (LRP) targeting. METHODS: Combined albumin-coated superparamagnetic iron oxide (SPIO), Carmustine (BCNU), and indocyanine green (ICG). Assessed morphology, size, Zeta potential, fluorescence, and drug encapsulation. Conducted in vitro fluorescence/MRI imaging and cell viability assays, and in vivo nanoprobe accumulation evaluation in brain tumors. RESULTS: ANG-BSA/BCNU/ICG MNPs exhibited superior targeting and cytotoxicity against GBM cells in vitro. In vivo, enhanced brain tumor accumulation during imaging was observed. CONCLUSION: This targeted imaging and drug delivery system holds promise for efficient GBM therapy and intraoperative localization, addressing Blood-brain barrier (BBB) limitations with precise drug delivery and imaging capabilities.

Decimeter-depth and polarization addressable color 3D meta-holography.

Fueled by the rapid advancement of nanofabrication, metasurface has provided unprecedented opportunities for 3D holography. Large depth 3D meta-holography not only greatly increases information storage capacity, but also enables distinguishing of the relative spatial relationship of 3D objects, which has important applications in fields like optical information storage and medical diagnosis. Although the methods based on Fresnel diffraction theory can reconstruct the real depth information of 3D objects, the maximum depth is only 2 mm. Here, we develop a 3D meta-holography based on angular spectrum diffraction theory to break through the depth limit. By developing the angular spectrum diffraction theory into meta-holography, the metasurface structure with independent polarization control is used to create a polarization multiplexing 3D meta-hologram. The fabricated amorphous silicon metasurface increases the depth range by 47.5 times and realizes 0.95 dm depth reconstruction for polarization independent and different color 3D meta-hologram in visible. Such polarization controlled large-depth color meta-holography is expected to open avenue for data storage, display, information security and virtual reality.

B4GALT1-dependent galectin-8 binding with TGF-ß receptor suppresses colorectal cancer progression and metastasis.

Transforming growth factor (TGF)-ß signaling is critical for epithelial-mesenchymal transition (EMT) and colorectal cancer (CRC) metastasis. Disruption of Smad-depednent TGF-ß signaling has been shown in CRC cells. However, TGF-ß receptor remains expressed on CRC cells. Here, we investigated whether the cooperation between tumor-associated N-glycosylation and a glycan-binding protein modulated the TGF-ß-driven signaling and metastasis of CRC. We showed that galectin-8, a galactose-binding lectin, hampered TGF-ß-induced EMT by interacting with the type II TGF-ß receptor and competing with TGF-ß binding. Depletion of galectin-8 promoted the migration of CRC cells by increasing TGF-ß-receptor-mediated RAS and Src signaling, which was attenuated after recombinant galectin-8 treatment. Treatment with recombinant galectin-8 also induces JNK-dependent apoptosis in CRC cells. The anti-migratory effect of galectin-8 depended on ß4-galactosyltransferase-I (B4GALT1), an enzyme involved in N-glycan synthesis. Increased B4GALT1 expression was observed in clinical CRC samples. Depletion of B4GALT1 reduced the metastatic potential of CRC cells. Furthermore, inducible expression of galectin-8 attenuated tumor development and metastasis of CRC cells in an intra-splenic injection model. Our results thus demonstrate that galectin-8 alters non-canonical TGF-ß response in CRC cells and suppresses CRC progression.

Longitudinal registration of thoracic CT images with radiation-induced lung diseases: A divide-and-conquer approach based on component structure wise registration using coherent point drift.

BACKGROUND AND OBJECTIVE: Registration of pulmonary computed tomography (CT) images with radiation-induced lung diseases (RILD) was essential to investigate the voxel-wise relationship between the formation of RILD and the radiation dose received by different tissues. Although various approaches had been developed for the registration of lung CTs, their performances remained clinically unsatisfactory for registration of lung CT images with RILD. The main difficulties arose from the longitudinal change in lung parenchyma, including RILD and volumetric change of lung cancers, after radiation therapy, leading to inaccurate registration and artifacts caused by erroneous matching of the RILD tissues. METHODS: To overcome the influence of the parenchymal changes, a divide-and-conquer approach rooted in the coherent point drift (CPD) paradigm was proposed. The proposed method was based on two kernel ideas. One was the idea of component structure wise registration. Specifically, the proposed method relaxed the intrinsic assumption of equal isotropic covariances in CPD by decomposing a lung and its surrounding tissues into component structures and independently registering the component structures pairwise by CPD. The other was the idea of defining a vascular subtree centered at a matched branch point as a component structure. This idea could not only provide a sufficient number of matched feature points within a parenchyma, but avoid being corrupted by the false feature points resided in the RILD tissues due to globally and indiscriminately sampling using mathematical operators. The overall deformation model was built by using the Thin Plate Spline based on all matched points. RESULTS: This study recruited 30 pairs of lung CT images with RILD, 15 of which were used for internal validation (leave-one-out cross-validation) and the other 15 for external validation. The experimental results showed that the proposed algorithm achieved a mean and a mean of maximum 1 % of average surface distances <2 and 8 mm, respectively, and a mean and a maximum target registration error <2 mm and 5 mm on both internal and external validation datasets. The paired two-sample t-tests corroborated that the proposed algorithm outperformed a recent method, the Stavropoulou's method, on the external validation dataset (p < 0.05). CONCLUSIONS: The proposed algorithm effectively reduced the influence of parenchymal changes, resulting in a reasonably accurate and artifact-free registration.

Predictors of Postoperative Outcomes after Arthroscopic Partial Meniscectomy: A Retrospective Analysis.

OBJECTIVE: Arthroscopic partial meniscectomy is a widely used surgical technique for treating meniscus injuries, while individual differences in postoperative outcomes remain a significant concern. This retrospective study aimed to identify the factors influencing clinical outcomes following arthroscopic partial meniscectomy. METHODS: We retrospectively examined the clinical data of 52 patients who underwent arthroscopic partial meniscectomy at our institution from January to May 2022. Observation indicators, including gender, age, type of medical insurance, various surgeons, the self-pay portion of hospital costs, and total hospital costs, were systematically recorded. Subjective symptoms were evaluated with ΔTenger, ΔLysholm, and International Knee Documentation Committee (IKDC) scores during follow-up. The trends of the above questionnaires and potential predictors were statistically evaluated through regression analysis. RESULTS: Binary logistic analysis revealed that female patients (OR: 32.42; 95% confidence interval [CI]: 2.22, 473.86) and higher preoperative visual analog scale (VAS) (odds ratio [OR]: 3.58; 95% CI: 1.55, 8.28) were significantly associated with FP Lysholm score. Similarly, patients with elevated preoperative VAS (OR: 1.47; 95% CI: 1.01, 2.15) were significantly more likely to have FP IKDC scores. Multiple linear regression analysis revealed that traumatic meniscus tear (ß = -0.324; 95% CI: -0.948, -0.036; p = 0.035) emerged as a negative independent predictor of ΔTegner, while higher preoperative VAS scores (ß = 0.330; 95% CI: 0.013, 0.217; p = 0.028) were identified as positive independent predictors of ΔTegner. The duration of symptoms (ß = -0.327; 95% CI: -0.010, -0.001; p = 0.023) had a negative impact on the ΔLysholm scores. Factors such as body mass index (BMI) (ß = -0.250; 95% CI: -1.000, -0.020; p = 0.042), duration of symptoms (ß = -0.302; 95% CI: -0.009, -0.001; p = 0.014), and preoperative VAS (ß = -0.332; 95% CI: -1.813, -0.250; p = 0.011) were negatively associated with ΔIKDC scores. CONCLUSION: The study offers insights into multiple factors for patient outcomes after arthroscopic partial meniscectomy. Orthopedic surgeons need to consider variables such as gender, BMI, duration of symptoms, preoperative VAS, and the traumatic/degenerative types of meniscal tears to optimize postoperative outcomes.

Predicting postoperative prognosis in clear cell renal cell carcinoma using a multiphase CT-based deep learning model.

BACKGROUND: Some clinicopathological risk stratification systems (CRSSs) such as the leibovich score have been used to predict the postoperative prognosis of patients with clear cell renal cell carcinoma (ccRCC), but there are no reliable noninvasive preoperative indicators for predicting postoperative prognosis in clinical practice. PURPOSE: To assess the value of a deep learning (DL) model based on CT images in predicting the postoperative prognosis of patients with ccRCC. MATERIALS AND METHODS: A total of 382 patients with ccRCC were retrospectively enrolled andallocated to training (n = 229) or testing (n = 153) cohorts at a 6:4 ratio. The features were extracted from precontrast-phase (PCP), corticomedullary-phase (CMP) and nephrographic-phase (NP) CT images with ResNet50, and then extreme learning machines (ELMs) were used to construct classification models. The DL model and Leibovich score were compared and combined. A receiver operating characteristic (ROC) curve and integrated discrimination improvement (IDI) were used to evaluate model performance. RESULTS: Compared with other single-phase DL models, the three-phase CT-based DL model achieved the best performance, with an area under the curve (AUC) of 0.839. Combining the three-phase DL model and the Leibovich score (AUC = 0.823) into a nomogram (AUC = 0.888) statistically improved performance (IDINomogram vs. Three-phase = 0.1358, IDINomogram vs. Leibovich = 0.1393, [Formula: see text]< 0.001). CONCLUSION: The CT-based DL model could be valuable for preoperatively predicting the prognosis of patients with ccRCC, and combining it with the Leibovich score can further improve its predictive performance.

Delta Radiomics Based on MRI for Predicting Axillary Lymph Node Pathologic Complete Response After Neoadjuvant Chemotherapy in Breast Cancer Patients.

PURPOSE: To develop and test a radiomics nomogram based on magnetic resonance imaging (MRI) and clinicopathological factors for predicting the axillary pathologic complete response (apCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients with axillary lymph node (ALN) metastases. MATERIALS AND METHODS: A total of 319 patients who underwent MRI examination and received NAC treatment were enrolled from two centers, and the presence of ALN metastasis was confirmed by biopsy pathology before NAC. The radiomics features were extracted from regions of interest of ALNs before (pre-radiomics) and after (post-radiomics) NAC. The difference of features before and after NAC, named delta radiomics, was calculated. The variance threshold, selectKbest and least absolute shrinkage and selection operator algorithm were used to select radiomics features. Radscore was calculated by a linear combination of selected features, weighted by their respective coefficients. The univariate and multivariate logistic regression was used to select the clinicopathological factors and radscores, and a radiomics nomogram was built by multivariable logistic regression analysis. The performance of the nomogram was evaluated by the area under the receiver operator characteristic curve (AUC), decision curve analysis (DCA) and calibration curves. Furthermore, to explore the biological basis of radiomics nomogram, 16 patients with RNA-sequence data were included for genetic analysis. RESULTS: The radiomics nomogram was constructed by two radscores (post- and delta- radscores) and one clinicopathological factor (progesterone hormone, PR), and showed powerful predictive performance in both internal and external test sets, with AUCs of 0.894 (95% confidence interval [CI], 0.877-0.959) and 0.903 (95% CI, 0.801-0.986), respectively. The calibration curves and DCA showed favorable consistency and clinical utility. With the assistance of nomogram, the rate of unnecessary ALND would be reduced from 60.42% to 21.88%, and the rate of final benefit rate would be increased from 39.58% to 70.83%. Moreover, genetic analysis revealed that high apCR prediction scores were associated with the upregulation of immune-mediated genes and pathways. CONCLUSION: The radiomics nomogram showed great performance in predicting apCR after NAC for breast cancer patients, which could help clinicians to identify patients with apCR and avoid unnecessary axillary lymph node dissection.

Health economic evaluation of an artificial intelligence (AI)-based rapid nutritional diagnostic system for hospitalised patients: A multicentre, randomised controlled trial.

BACKGROUND & AIMS: Malnutrition is prevalent among hospitalised patients, and increases the morbidity, mortality, and medical costs; yet nutritional assessments on admission are not routine. This study assessed the clinical and economic benefits of using an artificial intelligence (AI)-based rapid nutritional diagnostic system for routine nutritional screening of hospitalised patients. METHODS: A nationwide multicentre randomised controlled trial was conducted at 11 centres in 10 provinces. Hospitalised patients were randomised to either receive an assessment using an AI-based rapid nutritional diagnostic system as part of routine care (experimental group), or not (control group). The overall medical resource costs were calculated for each participant and a decision-tree was generated based on an intention-to-treat analysis to analyse the cost-effectiveness of various treatment modalities. Subgroup analyses were performed according to clinical characteristics and a probabilistic sensitivity analysis was performed to evaluate the influence of parameter variations on the incremental cost-effectiveness ratio (ICER). RESULTS: In total, 5763 patients participated in the study, 2830 in the experimental arm and 2933 in the control arm. The experimental arm had a significantly higher cure rate than the control arm (23.24% versus 20.18%; p = 0.005). The experimental arm incurred an incremental cost of 276.52 CNY, leading to an additional 3.06 cures, yielding an ICER of 90.37 CNY. Sensitivity analysis revealed that the decision-tree model was relatively stable. CONCLUSION: The integration of the AI-based rapid nutritional diagnostic system into routine inpatient care substantially enhanced the cure rate among hospitalised patients and was cost-effective. REGISTRATION: NCT04776070 (https://clinicaltrials.gov/study/NCT04776070).

Enhancing Activity and Stability of Pd-on-TiO2 Single-Atom Catalyst for Low-Temperature CO Oxidation through in Situ Local Environment Tailoring.

The development of efficient Pd single-atom catalysts for CO oxidation, crucial for environmental protection and fundamental studies, has been hindered by their limited reactivity and thermal stability. Here, we report a thermally stable TiO2-supported Pd single-atom catalyst that exhibits enhanced intrinsic CO oxidation activity by tunning the local coordination of Pd atoms via H2 treatment. Our comprehensive characterization reveals that H2-treated Pd single atoms have reduced nearest Pd-O coordination and form short-distanced Pd-Ti coordination, effectively stabilizing Pd as isolated atoms even at high temperatures. During CO oxidation, partial replacement of the Pd-Ti coordination by O or CO occurs. This unique Pd local environment facilitates CO adsorption and promotes the activity of the surrounding oxygen species, leading to superior catalytic performance. Remarkably, the turnover frequency of the H2-treated Pd single-atom catalyst at 120 °C surpasses that of the O2-treated Pd single-atom catalyst and the most effective Pd/Pt single-atom catalysts by an order of magnitude. These findings open up new possibilities for the design of high-performance single-atom catalysts for crucial industrial and environmental applications.

Advances in diffuse glioma assessment: preoperative and postoperative applications of chemical exchange saturation transfer.

Chemical Exchange Saturation Transfer (CEST) is a technique that uses specific off-resonance saturation pulses to pre-saturate targeted substances. This process influences the signal intensity of free water, thereby indirectly providing information about the pre-saturated substance. Among the clinical applications of CEST, Amide Proton Transfer (APT) is currently the most well-established. APT can be utilized for the preoperative grading of gliomas. Tumors with higher APTw signals generally indicate a higher likelihood of malignancy. In predicting preoperative molecular typing, APTw values are typically lower in tumors with favorable molecular phenotypes, such as isocitrate dehydrogenase (IDH) mutations, compared to IDH wild-type tumors. For differential diagnosis, the average APTw values of meningiomas are significantly lower than those of high-grade gliomas. Various APTw measurement indices assist in distinguishing central nervous system lesions with similar imaging features, such as progressive multifocal leukoencephalopathy, central nervous system lymphoma, solitary brain metastases, and glioblastoma. Regarding prognosis, APT effectively differentiates between tumor recurrence and treatment effects, and also possesses predictive capabilities for overall survival (OS) and progression-free survival (PFS).

In vitro study of ATP1A3 p.Ala275Pro mutant causing alternating hemiplegia of childhood and rapid-onset dystonia-parkinsonism.

Introduction: We previously reported that ATP1A3 c.823G>C (p.Ala275Pro) mutant causes varying phenotypes of alternative hemiplegia of childhood and rapid-onset dystonia-parkinsonism in the same family. This study aims to investigate the function of ATP1A3 c.823G>C (p.Ala275Pro) mutant at the cellular and zebrafish models. Methods: ATP1A3 wild-type and mutant Hela cell lines were constructed, and ATP1A3 mRNA expression, ATP1A3 protein expression and localization, and Na+-K+-ATPase activity in each group of cells were detected. Additionally, we also constructed zebrafish models with ATP1A3 wild-type overexpression (WT) and p.Ala275Pro mutant overexpression (MUT). Subsequently, we detected the mRNA expression of dopamine signaling pathway-associated genes, Parkinson's disease-associated genes, and apoptosisassociated genes in each group of zebrafish, and observed the growth, development, and movement behavior of zebrafish. Results: Cells carrying the p.Ala275Pro mutation exhibited lower levels of ATP1A3 mRNA, reduced ATP1A3 protein expression, and decreased Na+-K+-ATPase activity compared to wild-type cells. Immunofluorescence analysis revealed that ATP1A3 was primarily localized in the cytoplasm, but there was no significant difference in ATP1A3 protein localization before and after the mutation. In the zebrafish model, both WT and MUT groups showed lower brain and body length, dopamine neuron fluorescence intensity, escape ability, swimming distance, and average swimming speed compared to the control group. Moreover, overexpression of both wild-type and mutant ATP1A3 led to abnormal mRNA expression of genes associated with the dopamine signaling pathway and Parkinson's disease in zebrafish, and significantly upregulated transcription levels of bad and caspase-3 in the apoptosis signaling pathway, while reducing the transcriptional level of bcl-2 and the bcl-2/bax ratio. Conclusion: This study reveals that the p.Ala275Pro mutant decreases ATP1A3 protein expression and Na+/K+-ATPase activity. Abnormal expression of either wild-type or mutant ATP1A3 genes impairs growth, development, and movement behavior in zebrafish.

A rare concurrence of acute tubular necrosis and chronic glomerular sclerosis in a patient with wasp stings.

Wasp venom injections from wasp stings can damage several organs, most commonly the kidneys. Despite literature evidence, wasp sting-induced acute kidney injury (AKI) is rare and involves complex pathophysiological processes. While acute tubular necrosis (ATN) is the most prevalent histological result of wasp sting-induced AKI, uncommon combinations of chronic renal lesions have been described, alerting us to the patient's underlying illness. We report a 55-year-old hypertensive patient with unknown renal function who got AKI following multiple wasp stings. His renal function had not improved after continuous hemodialysis and plasma exchange; therefore, a kidney biopsy was performed. The pathology revealed that in addition to ATN, his kidney's distinguishing feature was a mix of chronic interstitial renal disease and chronic glomerulosclerosis. We think that his current renal pathological results were caused by hypertension in addition to wasp venom.

Genome-Wide Association Study of Susceptibility to Pseudomonas aeruginosa Infection in Cystic Fibrosis.

QUESTION: Pseudomonas aeruginosa (Pa) is a common pathogen that contributes to progressive lung disease in Cystic Fibrosis (CF). Genetic factors other than CF-causing CFTR variations contribute approximately 85% of the variation in chronic Pa infection age in CF according to twin studies, but the susceptibility loci remain unknown. Our objective is to advance understanding of the genetic basis of host susceptibility to Pa infection. MATERIALS AND METHODS: We conducted a genome-wide association study (GWAS) of chronic Pa infection age in 1037 Canadians with CF. We subsequently assessed the genetic correlation between chronic Pa infection age and lung function through polygenic risk score (PRS) analysis and inferred their causal relationship through bi-directional Mendelian Randomization analysis. RESULTS: Two novel genome-wide significant loci with lead SNPs rs62369766 (chr5p12; p-value= 1.98 ×10-8) and rs927553 (chr13q12.12; p-value= 1.91 × 10-8) were associated with chronic Pa infection age. The rs62369766 locus was validated using an independent French cohort (N=501). Furthermore, PRS constructed from CF lung function-associated SNPs was significantly associated with chronic Pa infection age (p-value=0.002). Finally, our analysis presented evidence for a causal effect of lung function on the chronic Pa infection age (Beta=0.782 years, p-value= 4.24 × 10-4). In the reverse direction, we observed a moderate effect (Beta=0.002, p-value=0.012). CONCLUSIONS: We identified two novel loci that are associated with chronic Pa infection age in individuals with CF. Additionally, we provided evidence of common genetic contributors and a potential causal relationship between Pa infection susceptibility and lung function in CF. Therapeutics targeting these genetic factors may delay the onset of chronic infections which accounts for significant remaining morbidity in CF.

Automated 3D Cobb Angle Measurement Using U-Net in CT Images of Preoperative Scoliosis Patients.

To propose a deep learning framework "SpineCurve-net" for automated measuring the 3D Cobb angles from computed tomography (CT) images of presurgical scoliosis patients. A total of 116 scoliosis patients were analyzed, divided into a training set of 89 patients (average age 32.4 ± 24.5 years) and a validation set of 27 patients (average age 17.3 ± 5.8 years). Vertebral identification and curve fitting were achieved through U-net and NURBS-net and resulted in a Non-Uniform Rational B-Spline (NURBS) curve of the spine. The 3D Cobb angles were measured in two ways: the predicted 3D Cobb angle (PRED-3D-CA), which is the maximum value in the smoothed angle map derived from the NURBS curve, and the 2D mapping Cobb angle (MAP-2D-CA), which is the maximal angle formed by the tangent vectors along the projected 2D spinal curve. The model segmented spinal masks effectively, capturing easily missed vertebral bodies. Spoke kernel filtering distinguished vertebral regions, centralizing spinal curves. The SpineCurve Network method's Cobb angle (PRED-3D-CA and MAP-2D-CA) measurements correlated strongly with the surgeons' annotated Cobb angle (ground truth, GT) based on 2D radiographs, revealing high Pearson correlation coefficients of 0.983 and 0.934, respectively. This paper proposed an automated technique for calculating the 3D Cobb angle in preoperative scoliosis patients, yielding results that are highly correlated with traditional 2D Cobb angle measurements. Given its capacity to accurately represent the three-dimensional nature of spinal deformities, this method shows potential in aiding physicians to develop more precise surgical strategies in upcoming cases.

Multiregional dynamic contrast-enhanced MRI-based integrated system for predicting pathological complete response of axillary lymph node to neoadjuvant chemotherapy in breast cancer: multicentre study.

BACKGROUND: The accurate evaluation of axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer holds great value. This study aimed to develop an artificial intelligence system utilising multiregional dynamic contrast-enhanced MRI (DCE-MRI) and clinicopathological characteristics to predict axillary pathological complete response (pCR) after NAC in breast cancer. METHODS: This study included retrospective and prospective datasets from six medical centres in China between May 2018 and December 2023. A fully automated integrated system based on deep learning (FAIS-DL) was built to perform tumour and ALN segmentation and axillary pCR prediction sequentially. The predictive performance of FAIS-DL was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RNA sequencing analysis were conducted on 45 patients to explore the biological basis of FAIS-DL. FINDINGS: 1145 patients (mean age, 50 years ±10 [SD]) were evaluated. Among these patients, 506 were in the training and validation sets (axillary pCR rate of 40.3%), 127 in the internal test set (axillary pCR rate of 37.8%), 414 in the pooled external test set (axillary pCR rate of 48.8%), and 98 in the prospective test set (axillary pCR rate of 43.9%). For predicting axillary pCR, FAIS-DL achieved AUCs of 0.95, 0.93, and 0.94 in the internal test set, pooled external test set, and prospective test set, respectively, which were also significantly higher than those of the clinical model and deep learning models based on single-regional DCE-MRI (all P < 0.05, DeLong test). In the pooled external and prospective test sets, the FAIS-DL decreased the unnecessary axillary lymph node dissection rate from 47.9% to 6.8%, and increased the benefit rate from 52.2% to 86.5%. RNA sequencing analysis revealed that high FAIS-DL scores were associated with the upregulation of immune-mediated genes and pathways. INTERPRETATION: FAIS-DL has demonstrated satisfactory performance in predicting axillary pCR, which may guide the formulation of personalised treatment regimens for patients with breast cancer in clinical practice. FUNDING: This study was supported by the National Natural Science Foundation of China (82371933), National Natural Science Foundation of Shandong Province of China (ZR2021MH120), Mount Taishan Scholars and Young Experts Program (tsqn202211378), Key Projects of China Medicine Education Association (2022KTM030), China Postdoctoral Science Foundation (314730), and Beijing Postdoctoral Research Foundation (2023-zz-012).