To identify important MRI features to differentiate hepatic mucinous cystic neoplasms from septated hepatic cysts based on random forest.

OBJECTIVE: To identify important MRI features to differentiate hepatic mucinous cystic neoplasms (MCN) from septated hepatic cysts (HC) using random forest and compared with logistic regression algorithm. METHODS: Pathologically diagnosed hepatic cysts and hepatic MCNs with pre-operative contrast-enhanced MRI in our hospital from 2010 to 2023 were collected and only septated lesions on enhanced MRI were enrolled. A total of 21 septated HC and 18 MCNs were included in this study. Eighteen MRI features were analyzed and top important features were identified based on random forest (RF) algorithm. The results were evaluated by the prediction performance of a RF model combining the important features and compared with the performance of the logistic regression (LR) algorithm. Finally, for each identified feature, diagnostic probability, sensitivity, and specificity were calculated and compared. RESULTS: Four variables, i.e., the septation arising from wall without indentation, multiseptate, intracapsular cyst sign, and solitary lesion were extracted as top important features with significance for MCNs by the random forest algorithm. The RF model using these variables had an AUC of 0.982 (0.95CI, 0.950-1.000), compared with the LR model based on two identified features with AUC of 0.931 (0.95CI, 0.846-1.000), p = 0.202. Among the four important features, multiseptate had the highest specificity (95.2%) and good sensitivity (72.2%, lower than the septation from wall without indentation, 94.4%) to diagnose MCNs. CONCLUSION: Four out of 18 MRI features were extracted as reliably important factors to differ hepatic MCNs from septated HC. The combination of these four features in a RF model could achieve satisfactory diagnostic efficacy.

A CT-based radiomics nomogram involving the cystic fluid area for differentiating appendiceal mucinous neoplasms from appendicitis with intraluminal fluid.

OBJECTIVE: To develop and validate a radiomics nomogram based on computed tomography (CT) to distinguish appendiceal mucinous neoplasms (AMNs) from appendicitis with intraluminal fluid (AWIF). METHOD: A total of 211 patients from two medical institutions were retrospectively analysed, of which 109 were pathologically confirmed as having appendicitis with concomitant CT signs of intraluminal fluid and 102 as having AMN. All patients were randomly assigned to a training (147 patients) or validation cohort (64 patients) at a 7:3 ratio. Radiomics features of the cystic fluid area of the appendiceal lesions were extracted from nonenhanced CT images using 3D Slicer software. Minimum redundancy maximum relevance and least absolute shrinkage and selection operator regression methods were employed to screen the radiomics features and develop a radiomics model. Combined radiomics nomogram and clinical-CT models were further developed based on the corresponding features selected after multivariate analysis. Lastly, receiver operating characteristic curves, and decision curve analysis (DCA) were used to assess the models' performances in the training and validation cohorts. RESULTS: A total of 851 radiomics features were acquired from the nonenhanced CT images. Subsequently, a radiomics model consisting of eight selected features was developed. The combined radiomics nomogram model comprised rad-score, age, and mural calcification, while the clinical-CT model contained age and mural calcification. The combined model achieved area under the curves (AUCs) of 0.945 (95% confidence interval [CI]: 0.895, 0.976) and 0.933 (95% CI: 0.841, 0.980) in the training and validation cohorts, respectively, which were larger than those obtained by the radiomics (training cohort: AUC, 0.915 [95% CI: 0.865, 0.964]; validation cohort: AUC, 0.912 [95% CI: 0.843, 0.981]) and clinical-CT models (training cohort: AUC, 0.884 [95% CI: 0.820, 0.931]; validation cohort: AUC, 0.767 [95% CI: 0.644, 0.863]). Finally, DCA showed that the clinical utility of the combined model was superior to that of the clinical CT and radiomics models. CONCLUSION: Our combined radiomics nomogram model constituting radiomics, clinical, and CT features exhibited good performance for differentiating AMN from AWIF, indicating its potential application in clinical decision-making.

MRI quantitative assessment of the effects of low-carbohydrate therapy on Hashimoto's thyroiditis.

Objective: Hashimoto's thyroiditis is an inflammatory disease, and research suggests that a low-carbohydrate diet may have potential anti-inflammatory effects. This study aims to utilize Dixon-T2-weighted imaging (WI) sequence for a semi-quantitative assessment of the impact of a low-carbohydrate diet on the degree of thyroid inflammation in patients with Hashimoto's thyroiditis. Methods: Forty patients with Hashimoto's thyroiditis were recruited for this study and randomly divided into two groups: one with a normal diet and the other with a low-carbohydrate diet. Antibodies against thyroid peroxidase (TPOAb) and thyroglobulin (TgAb) were measured for all participants. Additionally, thyroid water content was semi-quantitatively measured using Dixon-T2WI. The same tests and measurements were repeated for all participants after 6 months. Results: After 6 months of a low-carbohydrate diet, patients with Hashimoto's thyroiditis showed a significant reduction in thyroid water content (94.84 ± 1.57% vs 93.07 ± 2.05%, P < 0.05). Concurrently, a decrease was observed in levels of TPOAb and TgAb (TPOAb: 211.30 (92.63-614.62) vs 89.45 (15.9-215.67); TgAb: 17.05 (1.47-81.64) vs 4.1 (0.51-19.42), P < 0.05). In contrast, there were no significant differences in thyroid water content or TPOAb and TgAb levels for patients with Hashimoto's thyroiditis following a normal diet after 6 months (P < 0.05). Conclusion: Dixon-T2WI can quantitatively assess the degree of thyroid inflammation in patients with Hashimoto's thyroiditis. Following a low-carbohydrate diet intervention, there is a significant reduction in thyroid water content and a decrease in levels of TPOAb and TgAb. These results suggest that a low-carbohydrate diet may help alleviate inflammation in patients with Hashimoto's thyroiditis.

Insight into the solubilization mechanism of wheat gluten by protease modification from conformational change and molecular interaction perspective.

The low solubility limits the utilization of other functional characteristics of wheat gluten (WG). This study effectively improved the solubility of WG through protease modification and explored the potential mechanism of protease modification to enhance the solubility of WG, further stimulating the potential application of WG in the food industry. Solubility of WG modified with alkaline protease, complex protease, and neutral protease was enhanced by 98.99%, 54.59%, and 51.68%, respectively. Notably, the content of ß-sheet was reduced while the combined effect of hydrogen bond and ionic bond were increased after protease modification. Meanwhile, the reduced molecular size and viscoelasticity as well as the elevated surface hydrophobicity, thermostability, water absorption capacity, and crystallinity were observed in modified WG. Moreover, molecular docking indicated that protease was specifically bound to the amino acid residues of WG through hydrogen bonding, hydrophobic interaction, and salt bridge.

Remodeling mechanism of gel network structure of soy protein isolate amyloid fibrils mediated by cellulose nanocrystals.

The differences in the gelling properties of soy protein isolate (SPI) and soy protein isolate amyloid fibrils (SAFs) as well as the role of cellulose nanocrystals (CNC) in regulating their gel behaviors were investigated in this study. The binding of CNC to ß-conglycinin (7S), glycinin (11S), and SAFs was predominantly driven by non-covalent interactions. CNC addition reduced the particle size, turbidity, subunit segments, and crystallinity of SPI and SAFs, promoted the conversion of α-helix to ß-sheet, improved the thermal stability, exposed more tyrosine and tryptophan residues, and enhanced the intermolecular interactions. A more regular and ordered lamellar network structure was formed in the SAFs-CNC composite gel, which could be conducive to the improvement of gel quality. This study would provide theoretical reference for the understanding of the regulatory mechanism of protein amyloid fibrils gelation as well as the high-value utilization of SAFs-CNC complex as a functional protein-based material or food ingredient in food field.

Disrupted topologic efficiency of brain functional connectome in de novo Parkinson's disease with depression.

Growing evidence supports that depression in Parkinson's disease (PD) depends on disruptions in specific neural networks rather than regional dysfunction. According to the resting-state functional magnetic resonance imaging data, the study attempted to decipher the alterations in the topological properties of brain networks in de novo depression in PD (DPD). The study also explored the neural network basis for depressive symptoms in PD. We recruited 20 DPD, 37 non-depressed PD and 41 healthy controls (HC). The Graph theory and network-based statistical methods helped analyse the topological properties of brain functional networks and anomalous subnetworks across these groups. The relationship between altered properties and depression severity was also investigated. DPD revealed significantly reduced nodal efficiency in the left superior temporal gyrus. Additionally, DPD decreased five hubs, primarily located in the temporal-occipital cortex, and increased seven hubs, mainly distributed in the limbic cortico-basal ganglia circuit. The betweenness centrality of the left Medio Ventral Occipital Cortex was positively associated with depressive scores in DPD. In contrast to HC, DPD had a multi-connected subnetwork with significantly lower connectivity, primarily distributed in the visual, somatomotor, dorsal attention and default networks. Regional topological disruptions in the temporal-occipital region are critical in the DPD neurological mechanism. It might suggest a potential network biomarker among newly diagnosed DPD patients.

Optimize the pore size-pore distribution-pore geometry-porosity of 3D-printed porous tantalum to obtain optimal critical bone defect repair capability.

The treatment and reconstruction of large or critical size bone defects is a challenging clinical problem. Additive manufacturing breaks the technical difficulties of preparing complex conformation and anatomically matched personalized porous tantalum implants, but the ideal pore structure for 3D-printed porous tantalum in critical bone defect repair applications remains unclear. Guiding appropriate bone tissue regeneration by regulating proper pore size-pore distribution-pore geometry-porosity is a challenge for its fabrication and application. We fabricated porous tantalum (PTa) scaffolds with six different combinations of pore structures using powder bed laser melting (L-PBF) technology. In vitro biological experiments were conducted to systematically investigate the effects of pore structure characteristics on osteoblast behaviors, showing that the bionic trabecular structure with both large and small poress facilitated cell permeation, proliferation and differentiation compared to the cubic structure with uniform pore sizes. The osteogenesis of PTa with different porosity of trabecular structures was further investigated by a rabbit condyle critical bone defect model. Synthetically, T70% up-regulated the expression of osteogenesis-related genes (ALP, COLI, OCN, RUNX-2) and showed the highest bone ingrowth area and bone contact rate in vivo after 16 weeks, with the best potential for critical bone defect repair. Our results suggested that the bionic trabecular structure with a pore size distribution of 200-1200 µm, an average pore size of 700 µm, and a porosity of 70 % is the best choice for repairing critical bone defects, which is expected to guide the clinical application of clinical 3D-printed PTa scaffolds.

A CT-based nomogram established for differentiating gastrointestinal heterotopic pancreas from gastrointestinal stromal tumor: compared with a machine-learning model.

OBJECTIVE: To identify CT features and establish a nomogram, compared with a machine learning-based model for distinguishing gastrointestinal heterotopic pancreas (HP) from gastrointestinal stromal tumor (GIST). MATERIALS AND METHODS: This retrospective study included 148 patients with pathologically confirmed HP (n = 48) and GIST (n = 100) in the stomach or small intestine that were less than 3 cm in size. Clinical information and CT characteristics were collected. A nomogram on account of lasso regression and multivariate logistic regression, and a RandomForest (RF) model based on significant variables in univariate analyses were established. Receiver operating characteristic (ROC) curve, mean area under the curve (AUC), calibration curve and decision curve analysis (DCA) were carried out to evaluate and compare the diagnostic ability of models. RESULTS: The nomogram identified five CT features as independent predictors of HP diagnosis: age, location, LD/SD ratio, duct-like structure, and HU lesion/pancreas A. Five features were included in RF model and ranked according to their relevance to the differential diagnosis: LD/SD ratio, HU lesion/pancreas A, location, peritumoral hypodensity line and age. The nomogram and RF model yielded AUC of 0.951 (95% CI: 0.842-0.993) and 0.894 (95% CI: 0.766-0.966), respectively. The DeLong test found no statistically significant difference in diagnostic performance (p > 0.05), but DCA revealed that the nomogram surpassed the RF model in clinical usefulness. CONCLUSION: Two diagnostic prediction models based on a nomogram as well as RF method were reliable and easy-to-use for distinguishing between HP and GIST, which might also assist treatment planning.

Diagnostic Value of MRI Features in Dual-phenotype Hepatocellular Carcinoma: A Preliminary Study.

This study aimed to explore the magnetic resonance imaging (MRI) features of dual-phenotype hepatocellular carcinoma (DPHCC) and their diagnostic value.The data of 208 patients with primary liver cancer were retrospectively analysed between January 2016 and June 2021. Based on the pathological diagnostic criteria, 27 patients were classified into the DPHCC group, 113 patients into the noncholangiocyte-phenotype hepatocellular carcinoma (NCPHCC) group, and 68 patients with intrahepatic cholangiocarcinoma (ICC) were classified into the ICC group. Two abdominal radiologists reviewed the preoperative MRI features by a double-blind method. The MRI features and key laboratory and clinical indicators were compared between the groups. The potentially valuable MRI features and key laboratory and clinical characteristics for predicting DPHCC were identified by univariate and multivariate analyses, and the odds ratios (ORs) were recorded. In multivariate analysis, tumour without capsule (P = 0.046, OR = 9.777), dynamic persistent enhancement (P = 0.006, OR = 46.941), and targetoid appearance on diffusion-weighted imaging (DWI) (P = 0.021, OR = 30.566) were independently significant factors in the detection of DPHCC compared to NCPHCC. Serum alpha-fetoprotein (AFP) > 20 µg/L (P = 0.036, OR = 67.097) and prevalence of hepatitis B virus (HBV) infection (P = 0.020, OR = 153.633) were independent significant factors in predicting DPHCC compared to ICC. The differences in other tumour marker levels and imaging features between the groups were not significant. In MR enhanced and diffusion imaging, tumour without capsule, persistent enhancement and DWI targetoid findings, combined with AFP > 20 µg/L and HBV infection-positive laboratory results, can help to diagnose DPHCC and differentiate it from NCPHCC and ICC. These results suggest that clinical, laboratory and MRI features should be integrated to construct an AI diagnostic model for DPHCC.

Altered functional connectivity of the primary motor cortex in tremor dominant and postural instability gait difficulty subtypes of early drug-naive Parkinson's disease patients.

Background: The primary motor cortex (M1) is an important hub in the motor circuitry of Parkinson's disease (PD), but the subregions' function and their correlation to tremor dominant (TD) and postural instability and gait disturbance (PIGD) with PD remain unclear. This study aimed to determine whether the functional connectivity (FC) of the M1 subregions varied between the PD and PIGD subtypes. Methods: We recruited 28 TD patients, 49 PIGD patients, and 42 healthy controls (HCs). M1 was divided into 12 regions of interest using the Human Brainnetome Atlas template to compare FC among these groups. Results: Compared with HCs, TD and PIGD patients exhibited increased FC between the left upper limb region (A4UL_L) and the right caudate nucleus (CAU)/left putamen (PUT), between the right A4UL (A4UL_R) and the left anterior cingulate and paracingulate gyri (ACG)/bilateral cerebellum4_5 (CRBL4_5)/left PUT/right CAU/left supramarginal gyrus/left middle frontal gyrus (MFG), as well as decreased connectivity between the A4UL_L and the left postcentral gyrus and the bilateral cuneus, and between the A4UL_R and the right inferior occipital gyrus. TD patients showed increased FC between the right caudal dorsolateral area 6 (A6CDL_R) and the left ACG/right MFG, between the A4UL_L and the right CRBL6/right middle frontal gyrus, orbital part/bilateral inferior frontal gyrus, and orbital part (ORBinf), and between the A4UL_R and the left ORBinf/right MFG/right insula (INS). PIGD patients displayed increased connectivity between the A4UL_L and the left CRBL4_5. Compared with PIGD patients, TD patients exhibited increased connectivity between the A6CDL_R and the left ACG/right MFG and between the A4UL_R and the left ACG/left ORBinf/right INS/right MFG. Furthermore, in TD and PIGD groups, the FC strength between the A6CDL_R and right MFG was negatively correlated with PIGD scores, while the FC strength between the A4UL_R and left ORBinf/right INS was positively correlated with TD scores and tremor scores. Conclusion: Our results demonstrated that early TD and PIGD patients share some common injury and compensatory mechanisms. TD patients occupied more resources in the MFG, ORBinf, INS, and ACG, which can be used as biomarkers to distinguish them from PIGD patients.

Primary vaginal signet ring cell carcinoma.

Primary vaginal cancer is rare, accounting for only 2% of all gynecological malignant tumors. Primary vaginal cell carcinoma is mainly squamous cell carcinoma, accounting for about 90%, and adenocarcinoma only accounts for 8-10%. Primary signet ring cell carcinoma of vagina is rare and has not been reported in the literature. This paper reports a case of signet ring cell carcinoma in vagina.

A diagnostic scoring model of ENKTCL in the nose-Waldeyer's ring based on logistic regression: Differential diagnosis from DLBCL.

Objective: To establish a logistic regression model based on CT and MRI imaging features and Epstein-Barr (EB) virus nucleic acid to develop a diagnostic score model to differentiate extranodal NK/T nasal type (ENKTCL) from diffuse large B cell lymphoma (DLBCL). Methods: This study population was obtained from two independent hospitals. A total of 89 patients with ENKTCL (n = 36) or DLBCL (n = 53) from January 2013 to May 2021 were analyzed retrospectively as the training cohort, and 61 patients (ENKTCL=27; DLBCL=34) from Jun 2021 to Dec 2022 were enrolled as the validation cohort. All patients underwent CT/MR enhanced examination and EB virus nucleic acid test within 2 weeks before surgery. Clinical features, imaging features and EB virus nucleic acid results were analyzed. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors of ENKTCL and establish a predictive model. Independent predictors were weighted with scores based on regression coefficients. A receiver operating characteristic (ROC) curve was created to determine the diagnostic ability of the predictive model and score model. Results: We searched for significant clinical characteristics, imaging characteristics and EB virus nucleic acid and constructed the scoring system via multivariate logistic regression and converted regression coefficients to weighted scores. The independent predictors for ENKTCL diagnosis in multivariate logistic regression analysis, including site of disease (nose), edge of lesion (blurred), T2WI (high signal), gyrus like changes, EB virus nucleic acid (positive), and the weighted score of regression coefficient was 2, 3, 4, 3, 4 points. The ROC curves, AUCs and calibration tests were carried out to evaluate the scoring models in both the training cohort and the validation cohort. The AUC of the scoring model in the training cohort were 0.925 (95% CI, 0.906-0.990) and the cutoff point was 5 points. In the validation cohort, the AUC was 0.959 (95% CI, 0.915-1.000) and the cutoff value was 6 points. Four score ranges were as follows: 0-6 points for very low probability of ENKTCL, 7-9 points for low probability; 10-11 points for middle probability; 12-16 points for very high probability. Conclusion: The diagnostic score model of ENKTCL based on Logistic regression model which combined with imaging features and EB virus nucleic acid. The scoring system was convenient, practical and could significantly improve the diagnostic accuracy of ENKTCL and the differential diagnosis of ENKTCL from DLBCL.

Functional and structural alterations as diagnostic imaging markers for depression in de novo Parkinson's disease.

Background: Depression in Parkinson's disease (PD) is identified and diagnosed with behavioral observations and neuropsychological measurements. Due to the large overlaps of depression and PD symptoms in clinical manifestations, it is challenging for neurologists to distinguish and diagnose depression in PD (DPD) in the early clinical stage of PD. The advancement in magnetic resonance imaging (MRI) technology provides potential clinical utility in the diagnosis of DPD. This study aimed to explore the alterations of functional and structural MRI in DPD to produce neuroimaging markers in discriminating DPD from non-depressed PD (NDPD) and healthy controls (HC). Methods: We recruited 20 DPD, 37 NDPD, and 41 HC matched in age, gender, and education years. The patients' diagnosis with PD was de novo. The differences in regional homogeneity (ReHo), voxel-wise degree centrality (DC), cortical thickness, cortical gray matter (GM) volumes, and subcortical GM volumes among these groups were detected, and the relationship between altered indicators and depression was analyzed. Moreover, the receiver operating characteristic (ROC) analysis was performed to assess the diagnostic efficacy of altered indicators for DPD. Results: Compared to NDPD and HC, DPD showed significantly increased ReHo in left dorsolateral superior frontal gyrus (DSFG) and DC in left inferior temporal gyrus (ITG), and decreased GM volumes in left temporal lobe and right Amygdala. Among these altered indicators, ReHo value in left DSFG and DC values in left ITG and left DSFG were significantly correlated with the severity of depression in PD patients. Comparing DPD and NDPD, the ROC analysis revealed a better area under the curve value for the combination of ReHo value in left DSFG and DC value in left ITG, followed by each independent indicator. However, the difference is not statistically significant. Conclusion: This study demonstrates that both functional and structural impairments are present in DPD. Among them, ReHo value of left DSFG and DC value of left ITG are equally well suited for the diagnosis and differential diagnosis of DPD, with a combination of them being slightly preferable. The multimodal MRI technique represents a promising approach for the classification of subjects with PD.

GWAS of grain color and tannin content in Chinese sorghum based on whole-genome sequencing.

KEY MESSAGE: Seventy-three QTL related to grain color and tannin content were identified in Chinese sorghum accessions, and a new recessive allelic variant of TAN2 gene was discovered. Sorghum is mainly used for brewing distilled liquors in China. Since grain tannins play an important role in liquor brewing, accurately understanding the relationship between grain color and tannin content can provide basis for selection standards of tannin sorghum. We resequenced a panel of 242 Chinese sorghum accessions and performed population structure and genome-wide association study (GWAS) to identify quantitative trait locus (QTL) affecting pericarp color, testa pigment, and tannin content. Phylogenetic analysis, principal component analysis (PCA), and admixture model were used to infer population structure. Two distinct genetic sub-populations were identified according to their corresponding northern and southern geographic origin. To investigate the genetic basis of natural variation in sorghum grain color, GWAS with 2,760,264 SNPs was conducted in four environments using multiple models (Blink, FarmCPU, GLM, and MLM). Seventy-three QTL were identified to be associated for the color of exocarp, mesocarp, testa, and tannin content on all chromosomes except chromosome 5, of which 47 might be novel QTL. Some important QTL were found to colocalize with orthologous genes in the flavonoid biosynthetic pathway from other plants, including orthologous of Arabidopsis (Arabidopsis thaliana) TT2, TT7, TT12, TT16 and AT5G41220 (GST), as well as orthologous of rice (Oryza sativa) MYB61 and OsbHLH025. Our investigation of the variation in grain color and tannin content in Chinese sorghum germplasm may help guide future sorghum breeding for liquor brewing.

Aberrant inter-network functional connectivity in drug-naive Parkinson's disease patients with tremor dominant and postural instability and gait difficulty.

Background: Insight into neural mechanisms of tremor dominant (TD) and postural instability and gait disorder (PIGD) subtypes in Parkinson's disease (PD) is vital for understanding pathophysiological hypotheses underlying this phenotype. However, network disturbances and their correlation with motor subtypes of PD remain unclear. We aimed to investigate the alterations of intra- and inter-network functional connectivity (FC) in drug-naive PD patients with different motor subtypes. Methods: Resting-state functional magnetic resonance imaging was performed on 25 drug-naive PD patients with TD (PD-TD) and 40 drug-naive PD patients with PIGD (PD-PIGD), and 37 healthy controls (HCs) underwent. The following networks were extracted using independent component analysis: sensorimotor network (SMN), left executive control network (LECN), right executive control network, anterior salience network (aSN), posterior salience network (pSN), ventral attention network (VAN), dorsal attention network (DAN), default mode network (DMN), visual network, and auditory network (AN). We measured FC values within and between these networks. Results: There were no detectable variations in intra-network FC. PD-PIGD group demonstrated lower FC between aSN and pSN, as well as between VAN and DMN, in contrast to PD-TD group. Particularly, the FC strength between VAN and DMN was positively correlated with TD and tremor scores, and the best fitting classification models of TD and PIGD subtypes were based on the FC between aSN and pSN. Compared with HCs, both PD-TD and PD-PIGD patients displayed decreased FC between two SMN subnetworks, while PD-TD patients exhibited increased FC between the SMN subnetwork and pSN, and between LECN and VAN. Furthermore, PD-PIGD patients demonstrated decreased FC between the SMN subnetwork and AN. Conclusions: The altered FC between aSN and pSN can be an imaging marker to distinguish PD-TD from PD-PIGD. We for the first time disclosed that the PD-TD patients compensated by increasing attention resources and the PD-PIGD patients displayed reduced FC between SMN and AN. Our findings provide a basis for identification and precision treatment of PD motor subtypes.

Recent Advances in Well-Designed Therapeutic Nanosystems for the Pancreatic Ductal Adenocarcinoma Treatment Dilemma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with an extremely poor prognosis and low survival rate. Due to its inconspicuous symptoms, PDAC is difficult to diagnose early. Most patients are diagnosed in the middle and late stages, losing the opportunity for surgery. Chemotherapy is the main treatment in clinical practice and improves the survival of patients to some extent. However, the improved prognosis is associated with higher side effects, and the overall prognosis is far from satisfactory. In addition to resistance to chemotherapy, PDAC is significantly resistant to targeted therapy and immunotherapy. The failure of multiple treatment modalities indicates great dilemmas in treating PDAC, including high molecular heterogeneity, high drug resistance, an immunosuppressive microenvironment, and a dense matrix. Nanomedicine shows great potential to overcome the therapeutic barriers of PDAC. Through the careful design and rational modification of nanomaterials, multifunctional intelligent nanosystems can be obtained. These nanosystems can adapt to the environment's needs and compensate for conventional treatments' shortcomings. This review is focused on recent advances in the use of well-designed nanosystems in different therapeutic modalities to overcome the PDAC treatment dilemma, including a variety of novel therapeutic modalities. Finally, these nanosystems' bottlenecks in treating PDAC and the prospect of future clinical translation are briefly discussed.

Persistent Nocardia beijingensis infection in a patient with postoperative abscess and misuse of antibiotics in China.

Here we describe the first case of abscess infection caused by Nocardia beijingensis in China. The patient was immunocompetent but suffered from postoperative abscess for 6 years. This study highlights the necessity of long-term infected foci to be thoroughly examined to identify the pathogen, as well as the importance of accurate Nocardia identification and antimicrobial susceptibility tests for understanding the pathogen's epidemiology, clinical significance, and treatment strategy.

MRI Extraprostatic Extension Grade: Accuracy and Clinical Incremental Value in the Assessment of Extraprostatic Cancer.

Objective: The purpose was to compare the accuracy of extraprostatic extension (EPE) grade on MRI predicting EPE with Partin tables, Memorial Sloan Kettering Cancer Center nomogram (MSKCCn), and combined models and to analyze the clinical incremental value of EPE grade. Materials and Methods: 105 prostate cancer patients confirmed by pathology after radical prostatectomy in our hospital from 2017 to 2021 were selected. The clinical stage, PSA, Gleason score, number of positive biopsy cores, and percentage of positive biopsy cores were recorded. Evaluate EPE grade according to EPE grade criteria, and calculate the probability of predicting EPE with Partin tables and MSKCCn. EPE grade is combined with Partin tables and MSKCCn to construct EPE grade+Partin tables and EPE grade+MSKCCn models. Calculate the area under the curve (AUC), sensitivity, and specificity of EPE grade, Partin tables, MSKCCn, EPE grade+Partin tables, and EPE grade+MSKCCn and compare their diagnostic efficacy. The clinical decision curve was used to analyze the clinical net income of each prediction scheme. Results: The AUC of EPE grade was 0.79, Partin tables was 0.50, MSKCCn was 0.78, the EPE grade+Partin table model was 0.79, and the EPE grade+MSKCCn model was 0.83. After EPE grade was combined with Partin tables and MSKCCn, the diagnostic efficiency of clinical model was significantly improved (P < 0.05). There was no significant difference in the diagnostic efficacy of the combined model compared with the single EPE grade (P > 0.05). The calibration curve of the combined model shows that it has a good calibration degree for EPE. In the analysis of the decision curve, the net income of the EPE grade is higher than that of Partin tables and MSKCCn and is equal to the EPE grade+Partin tables and is slightly lower than that of EPE grade+MSKCCn. The clinical net income of the combined model is obviously higher than that of individual clinical models. Conclusion: The accuracy of EPE classification in predicting prostate cancer EPE is high, and combined with the clinical model, it can significantly improve the diagnostic efficiency of the clinical model and increase the clinical benefit.

[Effect of Down-Regulation of ANRIL on Proliferation and Apoptosis of Kasumi-1 Cells and Its Potential Mechanism].

OBJECTIVE: To investigate the down-regulation of ANRIL (Antisense non-coding RNA in the INK4 Locus) effects on proliferation and apoptosis of Kasumi-1 cells and its related molecular mechanism. METHODS: Recombinant lentivirus was used to construct ANRIL down-regulation Kasumi-1 cells (sh-ANRIL group) and its control cells (sh-NC group). A fluorescence microscope was used to observe the transfection efficiency, RT-qPCR was used to detect knockdown efficiency and ANRIL expression in PBMCs and MBMCs of patients with acute myeloid leukemia (AML). Proliferation and apoptosis of Kasumi-1 cells were assayed by CCK-8 method and flow cytometry. Western blot was employed to detect the expression of PI3K, AKT, p-AKT, and relevant protein after down-regulation of ANRIL in Kasumi-1 cells. RESULTS: ANRIL overexpressed significantly in PBMCs and MBMCs of patients with AML, the transfection efficiency of recombinant lentivirus carrying sh-ANRIL and sh-NC on Kasumi-1 cells exceeded 90%, and the knockdown efficiency was 70%. When DNR was administrated for 24, 48, and 72 hours, the cell inhibition rate of the sh-ANRIL group was (47.40±1.49)%, (69.11±0.51)% and (91.82±1.10)%, which were significantly higher than those of the sh-NC group, respectively (P<0.05). The apoptotic rate in the sh-ANRIL group was (10.29±0.58)%, which was significantly higher than (5.42±0.67)% of the sh-NC group (P<0.01). After DNR treatment for 24 hours, the apoptotic rate of the sh-ANRIL group was (54.41±1.69)%, which was significantly higher than (38.28±1.42)% of sh-NC group (P<0.001). Western blot revealed that the protein levels of PI3K, p-AKT, PCNA, and BCL-2 in the sh-ANRIL group were reduced significantly than those in the sh-NC group, while the BAX protein expression increased. CONCLUSION: ANRIL may affect the proliferation and apoptosis of Kasumi-1 cells through PI3K/AKT signaling pathway. ANRIL is a potential therapeutic target for AML.

Selection Signatures in Chinese Sorghum Reveals Its Unique Liquor-Making Properties.

Chinese sorghum (S. bicolor) has been a historically critical ingredient for brewing famous distilled liquors ever since Yuan Dynasty (749 ∼ 652 years BP). Incomplete understanding of the population genetics and domestication history limits its broad applications, especially that the lack of genetics knowledge underlying liquor-brewing properties makes it difficult to establish scientific standards for sorghum breeding. To unravel the domestic history of Chinese sorghum, we re-sequenced 244 Chinese sorghum lines selected from 16 provinces. We found that Chinese sorghums formed three distinct genetic sub-structures, referred as the Northern, the Southern, and the Chishui groups, following an obviously geographic pattern. These sorghum accessions were further characterized in liquor brewing traits and identified selection footprints associated with liquor brewing efficiency. An importantly selective sweep region identified includes several homologous genes involving in grain size, pericarp thickness, and architecture of inflorescence. Our result also demonstrated that pericarp strength rather than grain size determines the ability of the grains to resist repeated cooking during brewing process. New insight into the traits beneficial to the liquor-brewing process provides both a better understanding on Chinese sorghum domestication and a guidance on breeding sorghum as a multiple use crop in China.