Nuclear F-actin assembly on damaged chromatin is regulated by DYRK1A and Spir1 phosphorylation.

Nuclear actin-based movements support DNA double-strand break (DSB) repair. However, molecular determinants that promote filamentous actin (F-actin) formation on the damaged chromatin remain undefined. Here we describe the DYRK1A kinase as a nuclear activity that promotes local F-actin assembly to support DSB mobility and repair, accomplished in part by its targeting of actin nucleator spire homolog 1 (Spir1). Indeed, perturbing DYRK1A-dependent phosphorylation of S482 mis-regulated Spir1 accumulation at damaged-modified chromatin, and led to compromised DSB-associated actin polymerization and attenuated DNA repair. Our findings uncover a role of the DYRK1A-Spir1 axis in nuclear actin dynamics during early DSB responses, and highlight the intricate details of nuclear cytoskeletal network in DSB repair and genome stability maintenance.

Modeling multi-component separation in hydrophobic interaction chromatography with improved parameter-by-parameter estimation method.

Mechanistic models are powerful tools for chromatographic process development and optimization. However, hydrophobic interaction chromatography (HIC) mechanistic models lack an effective and logical parameter estimation method, especially for multi-component system. In this study, a parameter-by-parameter method for multi-component system (called as mPbP-HIC) was derived based on the retention mechanism to estimate the six parameters of the Mollerup isotherm for HIC. The linear parameters (ks,i and keq,i) and nonlinear parameters (ni and qmax,i) of the isotherm can be estimated by the linear regression (LR) and the linear approximation (LA) steps, respectively. The remaining two parameters (kp,i and kkin,i) are obtained by the inverse method (IM). The proposed method was verified with a two-component model system. The results showed that the model could accurately predict the protein elution at a loading of 10 g/L. However, the elution curve fitting was unsatisfactory for high loadings (12 g/L and 14 g/L), which is mainly attributed to the demanding experimental conditions of the LA step and the potential large estimation error of the parameter qmax. Therefore, the inverse method was introduced to further calibrate the parameter qmax, thereby reducing the estimation error and improving the curve fitting. Moreover, the simplified linear approximation (SLA) was proposed by reasonable assumption, which provides the initial guess of qmax without solving any complex matrix and avoids the problem of matrix unsolvable. In the improved mPbP-HIC method, qmax would be initialized by the SLA and finally determined by the inverse method, and this strategy was named as SLA+IM. The experimental validation showed that the improved mPbP-HIC method has a better curve fitting, and the use of SLA+IM reduces the error accumulation effect. In process optimization, the parameters estimated by the improved mPbP-HIC method provided the model with excellent predictive ability and reasonable extrapolation. In conclusion, the SLA+IM strategy makes the improved mPbP-HIC method more rational and can be easily applied to the practical separation of protein mixture, which would accelerate the process development for HIC in downstream of biopharmaceuticals.

Establishment and characterization of a novel multidrug-resistant pancreatic ductal adenocarcinoma cell line, PDAC-X1.

Drug resistance remains a significant challenge in the treatment of pancreatic cancer. The development of drug-resistant cell lines is crucial to understanding the underlying mechanisms of resistance and developing novel drugs to improve clinical outcomes. Here, a novel pancreatic cancer cell line, PDAC-X1, derived from Chinese patients has been established. PDAC-X1 was characterized by the immune phenotype, biology, genetics, molecular characteristics, and tumorigenicity. In vitro analysis revealed that PDAC-X1 cells exhibited epithelial morphology and cell markers (CK7 and CK19), expressed cancer-associated markers (E-cadherin, Vimentin, Ki-67, CEA, CA19-9), and produced pancreatic cancer-like organs in suspension culture. In vivo analysis showed that PDAC-X1 cells maintained tumorigenicity with a 100% tumor formation rate. This cell line exhibited a complex karyotype, dominated by subtriploid karyotypes. In addition, PDAC-X1 cells exhibited intrinsic multidrug resistance to multiple drugs, including gemcitabine, paclitaxel, 5-fluorouracil, and oxaliplatin. In conclusion, the PDAC-X1 cell line has been established and characterized, representing a useful and valuable preclinical model to study the underlying mechanisms of drug resistance and develop novel drug therapeutics to improve patient outcomes.

The comparative efficacy and safety of factor Xa inhibitors and warfarin for primary thromboprophylaxis in multiple myeloma patients undergoing immunomodulatory therapy.

There are limited data on the optimal choice of anticoagulation in multiple myeloma (MM) patients receiving immunomodulatory drugs (IMiDs). We conducted a propensity score-matched cohort study using the TriNetX database to compare the efficacy and safety of factor Xa inhibitors and warfarin in this patient population. Compared to warfarin, factor Xa inhibitors had a similar risk of deep vein thrombosis (hazard ratio [HR]: 1.11 [95% CI: 0.50-2.46]) or pulmonary embolism (HR: 1.08 [95% CI: 0.59-2.00]). There were no differences in the risk of gastrointestinal or intracranial bleeding. Factor Xa inhibitor-treated patients had lower all-cause mortality (HR: 0.56 [95% CI: 0.36-0.86]) compared with warfarin. These data suggest that factor Xa inhibitors had similar safety and efficacy compared with warfarin for MM patients on IMiDs.

Trade-offs of reproductive growth and Cd remobilization regulated Cd accumulation in wheat grains (Triticum aestivum L.).

Minimization of cadmium (Cd) accumulation in wheat grain (Triticum aestivum L.) is an important way to prevent Cd hazards to humans. However, little is known about the mechanisms of varietal variation of Cd accumulation in wheat grain. This study explores the physiological mechanisms of Cd bioaccumulation through field and hydroponic experiments on two wheat varieties of low-Cd-accumulating variety (L-6331) and high-Cd-accumulating variety (H-6049). Field study showed that average Cd accumulative rates in spikes of H-6049 were 1.57-fold of L-6331 after flowering, ultimately grain-Cd of H-6049 was 1.70-fold of L-6331 in Cd-contaminated farmland. The hydroponic experiment further confirmed that more vegetative tissues of L-6331 were involved in the remobilization of Cd, which jointly mitigated the process of Cd loaded to grains when leaf-cutting conducted after Cd stress. Additionally, the L1 and N1 of L-6331 play an especially important role in regulating Cd remobilization, and the larger EVB areas in N1 have the morphological feature that facilitates the transfer of Cd to L1. Overall results implied that low-Cd-accumulating variety initiated more trade-offs of reproductive growth and Cd remobilizatoin under Cd-stress after flowering compared with high-Cd-accumulating variety, and provided new insights into the processes of Cd loaded into wheat grains among different varieties.

Establishment and characterization of the PDAC-X3 cell line: a novel Chinese-origin pancreatic ductal adenocarcinoma cell line.

In this study, a novel pancreatic cancer cell line, termed pancreatic ductal adenocarcinoma (PDAC)-X3 cell line, was successfully derived from the primary tumor. Comprehensive analyses of its malignant phenotype, molecular properties, specific biomarkers, and histological features confirmed that PDAC-X3 cells serve as a valuable model for investigating the underlying mechanisms driving pancreatic carcinogenesis and advancing potential therapeutic strategies. The newly established cell line was continuously cultured for over 12 months and was stably passaged through more than 50 generations. Morphologically, PDAC-X3 cells displayed characteristics typical of epithelial tumors. The population doubling time for PDAC-X3 cells was determined to be 50 h. Karyotype analysis revealed that 75% of PDAC-X3 cells presented as hypotriploid, while 25% were sub-tetraploid, with representative karyotypes being 53 and XY der (1) inv (9) der (22). In suspension culture, PDAC-X3 cells efficiently formed organoids. Upon inoculation into BALB/C nude mice, these cells initiated the development of xenograft tumors, achieving a tumor formation rate of 33%. Morphologically, these xenografted tumors closely resembled the primary tumor. Drug sensitivity assays indicated that PDAC-X3 cells exhibited resistance to oxaliplatin but demonstrated sensitivity to 5-Fluorouracil (5-FU), gemcitabine, and paclitaxel. Immunohistochemical analysis revealed that CK7, CK19, E-cadherin, Vimentin, CA19-9 were positively expressed in PDAC-X3 cells. Meanwhile, the expression rate for Ki-67 was 30%, and that for CEA was not detected. Our findings underscore that PDAC-X3 represents a novel pancreatic cancer cell line, positioning it as a valuable model for basic research and the advancement of therapeutic strategies against pancreatic cancer.

Deep Eutectic Solvent-Assisted Corrosion Boosting Bulk FeCoNiCrMo High-Entropy Alloys as Highly Efficient Oxygen Evolution Reaction Catalyst.

The key to enhancing water electrolysis efficiency lies in selecting highly efficient catalysts. Currently, high-entropy alloys (HEAs) are utilized in electrocatalysis applications owing to their diverse elemental composition, disordered elemental distribution, and the high solubility of each element, endowing them with excellent catalytic performance. The experiments were conducted using isoatomic FeNiCrMo HEA as a precursor, with a high-activity three-dimensional nanoporous structure rapidly synthesized via electrochemical one-step dealloying in a choline chloride-thiourea (ChCl-TU) deep eutectic solvent (DES). The results indicate that the dealloyed Fe20Co20Ni20Cr20Mo20 HEA mainly consists of two phases: face-centered cubic and σ phases. The imbalance in the distribution of elements in these two phases leads to quite different corrosion speeds with the FCC phase being preferentially corroded. Furthermore, synergistic electron coupling between surface atoms in the three-dimensional nanoporous structure strengthens the behavior of the oxygen evolution reaction (OER). At a current density of 40 mA cm-2, the overpotential after dealloying decreased to 370 mV, demonstrating excellent stability. The technique demonstrated in this work provides a novel approach to improve the catalytic activity of OER.

NMR-Based Chiral Discrimination of Bulky Amines with a 19F-Tagged NNO Pincer Complex.

Within pharmaceutical research, ensuring the enantiomeric purity of chiral compounds is critical. Specifically, chiral amines are a crucial category of compounds, due to their extensive therapeutic uses. However, the enantiomeric analysis of these compounds, particularly those with significant steric hindrance, remains a challenge. To address this issue, our research introduces a novel chiral 19F-tagged NNO palladium pincer probe, strategically engineered with an open binding site to accommodate bulky amines. This probe facilitates the enantiodifferentiation of such amines, as evidenced by the distinct 19F NMR signals generated by the enantiomers. Moreover, our findings highlight the probe's applicability in the chiral discrimination of various psychoactive substances, underscoring its potential for the identification of illegal stimulant use and contributing to forensic investigations.

Erratum: Therapeutic potential of EGFR/mTOR/Nf-kb targeting small molecule for the treatment of non-small cell lung cancer.

[This corrects the article on p. 2598 in vol. 13, PMID: 37424807.].

Oral mucosal lesions triage via YOLOv7 models.

BACKGROUND/PURPOSE: The global incidence of lip and oral cavity cancer continues to rise, necessitating improved early detection methods. This study leverages the capabilities of computer vision and deep learning to enhance the early detection and classification of oral mucosal lesions. METHODS: A dataset initially consisting of 6903 white-light macroscopic images collected from 2006 to 2013 was expanded to over 50,000 images to train the YOLOv7 deep learning model. Lesions were categorized into three referral grades: benign (green), potentially malignant (yellow), and malignant (red), facilitating efficient triage. RESULTS: The YOLOv7 models, particularly the YOLOv7-E6, demonstrated high precision and recall across all lesion categories. The YOLOv7-D6 model excelled at identifying malignant lesions with notable precision, recall, and F1 scores. Enhancements, including the integration of coordinate attention in the YOLOv7-D6-CA model, significantly improved the accuracy of lesion classification. CONCLUSION: The study underscores the robust comparison of various YOLOv7 model configurations in the classification to triage oral lesions. The overall results highlight the potential of deep learning models to contribute to the early detection of oral cancers, offering valuable tools for both clinical settings and remote screening applications.

Risk factors for AKI or mortality and long-term follow-up in COVID-19 infected patients in the era nefore vaccination.

BACKGROUND: Acute kidney injury (AKI) is a severe complication of coronavirus disease 2019 (COVID-19) and is associated with a higher risk of mortality. Understanding the risk factors contributing to COVID-19-related AKI and mortality before vaccination is important for the initiation of preventative measures and early treatment strategies. METHODS: This study included patients aged ≥18 years diagnosed with COVID-19 through polymerase chain reaction from May 2020 to July 2021, admitted in three local hospitals in Taiwan, with an extended follow-up until June 30, 2022. A median follow-up period of 250 days was used to assess AKI development and mortality. AKI was defined according to the Kidney Disease Improving Global Outcomes criteria. Multivariate Cox regression analysis of AKI and mortality-related risk factors was performed. RESULTS: Of the 720 hospitalized patients with COVID-19, 90 (22%) developed AKI. Moreover, 80%, 10.1%, and 8.9% of the patients had stage 1, 2, and 3 AKI, respectively. Patients with stage 1-3 AKI had significantly lower survival rates than those without AKI (p = 0.0012). The mean duration of post-admission AKI occurrence was 9.50 ± 11.32 days. Older age, hypoalbuminemia, and higher D-dimer and ferritin levels were associated with COVID-19 mortality. In COVID-19 AKI, in addition to older age and high D-dimer and ferritin levels, chronic kidney disease emerged as an independent risk factor. CONCLUSION: COVID-19-related AKI develops early, exhibits a temporal association with respiratory failure, and is linked to an unfavorable prognosis. The mortality rate increased according to the AKI stage (p = 0.0012). Age; albumin, D-dimer, and ferritin levels; and the underlying chronic kidney disease status upon admission are crucial factors for predicting AKI development, which increases the mortality risk. Monitoring the renal function not only within 10 days of COVID-19 onset, but also within one month after the disease onset.

LARP3, LARP7, and MePCE are involved in the early stage of human telomerase RNA biogenesis.

Human telomerase assembly is a highly dynamic process. Using biochemical approaches, we find that LARP3 and LARP7/MePCE are involved in the early stage of human telomerase RNA (hTR) and that their binding to RNA is destabilized when the mature form is produced. LARP3 plays a negative role in preventing the processing of the 3'-extended long (exL) form and the binding of LARP7 and MePCE. Interestingly, the tertiary structure of the exL form prevents LARP3 binding and facilitates hTR biogenesis. Furthermore, low levels of LARP3 promote hTR maturation, increase telomerase activity, and elongate telomeres. LARP7 and MePCE depletion inhibits the conversion of the 3'-extended short (exS) form into mature hTR and the cytoplasmic accumulation of hTR, resulting in telomere shortening. Taken together our data suggest that LARP3 and LARP7/MePCE mediate the processing of hTR precursors and regulate the production of functional telomerase.

Dental Age Estimation in Northern Chinese Han Children and Adolescents Using Demirjian's Method Combined with Machine Learning Algorithms.

OBJECTIVES: To investigate the application value of combining the Demirjian's method with machine learning algorithms for dental age estimation in northern Chinese Han children and adolescents. METHODS: Oral panoramic images of 10 256 Han individuals aged 5 to 24 years in northern China were collected. The development of eight permanent teeth in the left mandibular was classified into different stages using the Demirjian's method. Various machine learning algorithms, including support vector regression (SVR), gradient boosting regression (GBR), linear regression (LR), random forest regression (RFR), and decision tree regression (DTR) were employed. Age estimation models were constructed based on total, female, and male samples respectively using these algorithms. The fitting performance of different machine learning algorithms in these three groups was evaluated. RESULTS: SVR demonstrated superior estimation efficiency among all machine learning models in both total and female samples, while GBR showed the best performance in male samples. The mean absolute error (MAE) of the optimal age estimation model was 1.246 3, 1.281 8 and 1.153 8 years in the total, female and male samples, respectively. The optimal age estimation model exhibited varying levels of accuracy across different age ranges, which provided relatively accurate age estimations in individuals under 18 years old. CONCLUSIONS: The machine learning model developed in this study exhibits good age estimation efficiency in northern Chinese Han children and adolescents. However, its performance is not ideal when applied to adult population. To improve the accuracy in age estimation, the other variables can be considered.

Visible light-mediated aza Paternò-Büchi reaction of acyclic oximes and alkenes to azetidines.

The aza Paternò-Büchi reaction is a [2+2]-cycloaddition reaction between imines and alkenes that produces azetidines, four-membered nitrogen-containing heterocycles. Currently, successful examples rely primarily on either intramolecular variants or cyclic imine equivalents. To unlock the full synthetic potential of aza Paternò-Büchi reactions, it is essential to extend the reaction to acyclic imine equivalents. Here, we report that matching of the frontier molecular orbital energies of alkenes with those of acyclic oximes enables visible light-mediated aza Paternò-Büchi reactions through triplet energy transfer catalysis. The utility of this reaction is further showcased in the synthesis of epi-penaresidin B. Density functional theory computations reveal that a competition between the desired [2+2]-cycloaddition and alkene dimerization determines the success of the reaction. Frontier orbital energy matching between the reactive components lowers transition-state energy (ΔGǂ) values and ultimately promotes reactivity.

Inhibiting mitochondrial citrate shuttling induces hepatic triglyceride deposition in Nile tilapia (Oreochromis niloticus) through lipid anabolic remodeling.

The solute carrier family 25 member 1 (Slc25a1)-dependent mitochondrial citrate shuttle is responsible for exporting citrate from the mitochondria to the cytoplasm for supporting lipid biosynthesis and protein acetylation. Previous studies on Slc25a1 concentrated on pathological models. However, the importance of Slc25a1 in maintaining metabolic homeostasis under normal nutritional conditions remains poorly understood. Here, we investigated the mechanism of mitochondrial citrate shuttle in maintaining lipid metabolism homeostasis in male Nile tilapia (Oreochromis niloticus). To achieve the objective, we blocked the mitochondrial citrate shuttle by inhibiting Slc25a1 under normal nutritional conditions. Slc25a1 inhibition was established by feeding Nile tilapia with 250 mg/kg 1,2,3-benzenetricarboxylic acid hydrate for 6 weeks or intraperitoneal injecting them with dsRNA to knockdown slc25a1b for 7 days. The Nile tilapia with Slc25a1 inhibition exhibited an obesity-like phenotype accompanied by fat deposition, liver damage and hyperglycemia. Moreover, Slc25a1 inhibition decreased hepatic citrate-derived acetyl-CoA, but increased hepatic triglyceride levels. Furthermore, Slc25a1 inhibition replenished cytoplasmic acetyl-CoA through enhanced acetate pathway, which led to hepatic triglycerides accumulation. However, acetate-derived acetyl-CoA caused by hepatic Slc25a1 inhibition did not activate de novo lipogenesis, but rather modified protein acetylation. In addition, hepatic Slc25a1 inhibition enhanced fatty acids esterification through acetate-derived acetyl-CoA, which increased Lipin1 acetylation and its protein stability. Collectively, our results illustrate that inhibiting mitochondrial citrate shuttle triggers lipid anabolic remodeling and results in lipid accumulation, indicating the importance of mitochondrial citrate shuttle in maintaining lipid metabolism homeostasis.

Natural lignin nanoparticles target tumor by saturating the phagocytic capacity of Kupffer cells in the liver.

Ligand-receptor recognition serves as the fundamental driving force for active targeting, yet it is still constrained by off-target effects. Herein, we demonstrate that circumventing or blocking the mononuclear phagocyte system (MPS) are both viable strategies to address off-target effects. Naturally derived lignin nanoparticles (LNPs) show great potential to block MPS due to its good stability, low toxicity, and degradability. We further demonstrate the impact of LNPs dosage on in vivo tumor targeting and antitumor efficacy. Our results show that a high dose of LNPs (300 mg/kg) leads to significant accumulation at the tumor site for a duration of 14 days after intravenous administration. In contrast, the low-dose counterparts (e.g., 50, 150 mg/kg) result in almost all LNPs accumulating in the liver. This discovery indicates that the liver is the primary site of LNP capture, leaving only the surplus LNPs the chance to reach the tumor. In addition, although cell membrane-engineered LNPs can rapidly penetrate tumors, they are still prone to capture by the liver during subsequent circulation in the bloodstream. Excitingly, comparable therapeutic efficacy is obtained for the above two strategies. Our findings may offer valuable insights into the targeted delivery of drugs for disease treatment.

A Camelid-Derived STAT-Specific Nanobody Inhibits Neuroinflammation and Ameliorates Experimental Autoimmune Encephalomyelitis (EAE).

Proinflammatory T-lymphocytes recruited into the brain and spinal cord mediate multiple sclerosis (MS) and currently there is no cure for MS. IFN-γ-producing Th1 cells induce ascending paralysis in the spinal cord while IL-17-producing Th17 cells mediate cerebellar ataxia. STAT1 and STAT3 are required for Th1 and Th17 development, respectively, and the simultaneous targeting of STAT1 and STAT3 pathways is therefore a potential therapeutic strategy for suppressing disease in the spinal cord and brain. However, the pharmacological targeting of STAT1 and STAT3 presents significant challenges because of their intracellular localization. We have developed a STAT-specific single-domain nanobody (SBT-100) derived from camelids that targets conserved residues in Src homolog 2 (SH2) domains of STAT1 and STAT3. This study investigated whether SBT-100 could suppress experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. We show that SBT-100 ameliorates encephalomyelitis through suppressing the expansion of Th17 and Th1 cells in the brain and spinal cord. Adoptive transfer experiments revealed that lymphocytes from SBT-100-treated EAE mice have reduced capacity to induce EAE, indicating that the immunosuppressive effects derived from the direct suppression of encephalitogenic T-cells. The small size of SBT-100 makes this STAT-specific nanobody a promising immunotherapy for CNS autoimmune diseases, including multiple sclerosis.

Low Levels of IgM Recognizing 4-Hydroxy-2-Nonenal-Modified Apolipoprotein A-I Peptide and Its Association with the Severity of Coronary Artery Disease in Taiwanese Patients.

Autoantibodies against apolipoprotein A-I (ApoA-I) are associated with cardiovascular disease risks. We aimed to examine the 4-hydroxy-2-nonenal (HNE) modification of ApoA-I in coronary artery disease (CAD) and evaluate the potential risk of autoantibodies against their unmodified and HNE-modified peptides. We assessed plasma levels of ApoA-I, HNE-protein adducts, and autoantibodies against unmodified and HNE-peptide adducts, and significant correlations and odds ratios (ORs) were examined. Two novel CAD-specific HNE-peptide adducts, ApoA-I251-262 and ApoA-I70-83, were identified. Notably, immunoglobulin G (IgG) anti-ApoA-I251-262 HNE, IgM anti-ApoA-I70-83 HNE, IgG anti-ApoA-I251-262, IgG anti-ApoA-I70-83, and HNE-protein adducts were significantly correlated with triglycerides, creatinine, or high-density lipoprotein in CAD with various degrees of stenosis (<30% or >70%). The HNE-protein adduct (OR = 2.208-fold, p = 0.020) and IgM anti-ApoA-I251-262 HNE (2.046-fold, p = 0.035) showed an increased risk of progression from >30% stenosis in CAD. HNE-protein adducts and IgM anti-ApoA-I251-262 HNE may increase the severity of CAD at high and low levels, respectively.

Deep Learning-Based Surgical Treatment Recommendation and Nonsurgical Prognosis Status Classification for Scaphoid Fractures by Automated X-ray Image Recognition.

Biomedical information retrieval for diagnosis, treatment and prognosis has been studied for a long time. In particular, image recognition using deep learning has been shown to be very effective for cancers and diseases. In these fields, scaphoid fracture recognition is a hot topic because the appearance of scaphoid fractures is not easy to detect. Although there have been a number of recent studies on this topic, no studies focused their attention on surgical treatment recommendations and nonsurgical prognosis status classification. Indeed, a successful treatment recommendation will assist the doctor in selecting an effective treatment, and the prognosis status classification will help a radiologist recognize the image more efficiently. For these purposes, in this paper, we propose potential solutions through a comprehensive empirical study assessing the effectiveness of recent deep learning techniques on surgical treatment recommendation and nonsurgical prognosis status classification. In the proposed system, the scaphoid is firstly segmented from an unknown X-ray image. Next, for surgical treatment recommendation, the fractures are further filtered and recognized. According to the recognition result, the surgical treatment recommendation is generated. Finally, even without sufficient fracture information, the doctor can still make an effective decision to opt for surgery or not. Moreover, for nonsurgical patients, the current prognosis status of avascular necrosis, non-union and union can be classified. The related experimental results made using a real dataset reveal that the surgical treatment recommendation reached 80% and 86% in accuracy and AUC (Area Under the Curve), respectively, while the nonsurgical prognosis status classification reached 91% and 96%, respectively. Further, the methods using transfer learning and data augmentation can bring out obvious improvements, which, on average, reached 21.9%, 28.9% and 5.6%, 7.8% for surgical treatment recommendations and nonsurgical prognosis image classification, respectively. Based on the experimental results, the recommended methods in this paper are DenseNet169 and ResNet50 for surgical treatment recommendation and nonsurgical prognosis status classification, respectively. We believe that this paper can provide an important reference for future research on surgical treatment recommendation and nonsurgical prognosis classification for scaphoid fractures.