Imaging classification of prostate cancer with extracapsular extension and its impact on positive surgical margins after laparoscopic radical prostatectomy.

Abstract: To explore the impact of different imaging classifications of prostate cancer (PCa) with extracapsular extension (EPE) on positive surgical margins (PSM) after laparoscopic radical prostatectomy. Methods: Clinical data were collected for 114 patients with stage PT3a PCa admitted to Ningbo Yinzhou No. 2 Hospital from September 2019 to August 2023. Radiologists classified the EPE imaging of PCa into Type I, Type II, and Type III. A chi-square test or t-test was employed to analyze the factors related to PSM. Multivariate regression analysis was conducted to determine the factors associated with PSM. Receiver operating characteristic curve analysis was used to calculate the area under the curve and evaluate the diagnostic performance of our model. Clinical decision curve analysis was performed to assess the clinical net benefit of EPE imaging classification, biopsy grade group (GG), and combined model. Results: Among the 114 patients, 58 had PSM, and 56 had negative surgical margins. Multivariate analysis showed that EPE imaging classification and biopsy GG were risk factors for PSM after laparoscopic radical prostatectomy. The areas under the curve for EPE imaging classification and biopsy GG were 0.677 and 0.712, respectively. The difference in predicting PSM between EPE imaging classification and biopsy GG was not statistically significant (P>0.05). However, when used in combination, the diagnostic efficiency significantly improved, with an increase in the area under the curve to 0.795 (P<0.05). The clinical decision curve analysis revealed that the clinical net benefit of the combined model was significantly higher than that of EPE imaging classification and biopsy GG. Conclusions: EPE imaging classification and biopsy GG were associated with PSM after laparoscopic radical prostatectomy, and their combination can significantly improve the accuracy of predicting PSM.

Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters.

Abstract: This study aimed to investigate the independent clinical, pathological, and radiological factors associated with extracapsular extension in radical prostatectomy specimens and to improve the accuracy of predicting extracapsular extension of prostate cancer before surgery. Methods: From August 2018 to June 2023, the clinical and pathological data of 229 patients with confirmed prostate cancer underwent radical prostatectomy from The Second Hospital of Yinzhou. The patients' multiparametric magnetic resonance imaging data were graded using the Likert scale. The chi-square or independent-sample T-test was used to analyze the related factors for an extracapsular extension. Multivariate analysis was used to identify independent factors associated with extracapsular extension in prostate cancer. Additionally, receiver operating characteristic curve analysis was used to calculate the area under the curve and assess the diagnostic performance of our model. The clinical decision curve was used to analyze the clinical net income of Likert scale, biopsy positive rate, biopsy GG, and combined mode. Results: Of the 229 patients, 52 had an extracapsular extension, and 177 did not. Multivariate analysis showed that the Likert scale score, biopsy grade group and biopsy positive rate were independent risk factors for extracapsular extension in prostate cancer. The area under the curves for the Likert scale score, biopsy grade group, and biopsy positive rate were 0.802, 0.762, and 0.796, respectively. Furthermore, there was no significant difference in the diagnostic efficiency for extracapsular extension (P>0.05). However, when these three factors were combined, the diagnostic efficiency was significantly improved, and the area under the curve increased to 0.905 (P<0.05). In the analysis of the decision curve, The clinical net income of the combined model is obviously higher than that of Likert scale, biopsy positive rate, and biopsy GG. Conclusion: The Likert scale, biopsy grade group and biopsy positive rate are independent risk factors for extracapsular extension in prostate cancer, and their combination can significantly improve the diagnostic efficiency for an extracapsular extension.

[A V-Y shaped flap with digital artery nerve at metacarpophalangeal joint was used to repair the defect of middle and distal phalanx].

OBJECTIVE: To explore a surgical method for the reconstruction of volar soft tissue defect and sensory and vascular repair in middle and far phalangeal digits. METHODS: From January 2016 to January 2020, a total of 14 patients , 9 males and 5 females, ages ranging from 22 to 69 years old, and with volar soft tissue defects in the middle and distal digits 2 to 4, underwent surgical reconstruction using the V-Y shaped flap with digital artery and nerve at the metacarpophalangeal joint. The defect area was (2.0~2.5) cm×(1.5 ~2.0) cm. The procedure involved the harvest of a V-Y shaped flap with the digital artery and nerve from the metacarpophalangeal joint. Flap design, dissection of blood vessels and nerves, and anastomosis with the digital artery and nerve were performed according to a standardized protocol., Functional exercise of affected finger was initiated 3 weeks postoperatively. Subsequent assessments were conducted to evaluate finger pulp sensation, shape and other relevant parameters. According to the upper extremity functional evaluation standard set up by Hand Surgery Branch of Chinese Medical Association, the surgical outcomes were evaluated. RESULTS: All 14 cases demonstrated successful tissue transplantation, , with immediate recovery of sensation observed in 10 cases with distal finger pulp defects. Four patients with middle phalangeal defects experienced gradual sensory recovery within 2 to 3 months postoperatively. Thirteen patients were followed up for a mean duration of (8.8 ± 4.49) months, during which satisfactory outcomes were observed. The average two-point resolution of the finger pulp was 4-6mm, and sensory function evaluation yielded a score of S3 or above. Patients exhibited realistic finger shape, normal skin color and temperature, good wear resistance, and cold resistance. Furthermore, finger joint function was essentially normal. CONCLUSION: The V-Y shaped flap with digital artery and nerve at the metacarpophalangeal joint offers a suitable solution for repairing the defect of the middle or distal phalangeal finger. This technique is characterized by its simplicity, low risk, and favorable outcomes, including restored finger shape, blood supply and sensation. Moreover, high patient satisfaction was achieved.

A Class of Enantiomerically Pure Bis-oxamide Palladium Complexes: Modular Synthesis via Domino C(sp2)-H Bond Arylation and Photophysical Property.

A one-pot, five-step domino reaction was developed for the arylation of bis-oxamides derived from optically pure 1,2-diphenylethylenediamine, leading to the formation of a series of chiral bis-oxalamide palladium(II) complexes bearing tetraaryl-conjugated substituents in good yields. In addition, these palladium(II) complexes exhibited perceptible blue fluorescence under ultraviolet light irradiation.

Chiral N-Heterocyclic-Carbene-Catalyzed Cascade Asymmetric Desymmetrization of Cyclopentenediones with Enals: Access to Optically Active 1,3-Indandione Derivatives.

A chiral N-heterocyclic-carbene-catalyzed cascade asymmetric desymmetrization reaction of cyclopentenediones with enals has been successfully initiated, followed with tandem aldol annulation, aromatization, as well as sequential methylation. The reactions proceeded well under mild reaction conditions, with broad substrate scope and good functional group tolerance, providing a rapid access to highly functionalized chiral 2,2-disubstituted 1,3-indandione derivatives containing an all-carbon quaternary stereogenic center in moderate to good yields with high enantioselectivities.

Stable Diindeno-Fused Corannulene Regioisomers with Open-Shell Singlet Ground States and Large Diradical Characters.

The synthesis of open-shell polycyclic hydrocarbons with large diradical characters is challenging because of their high reactivities. Herein, two diindeno-fused corannulene regioisomers DIC-1 and DIC-2, curved fragments of fullerene C104 , were synthesized that exhibit open-shell singlet ground states. The incorporation of the curved and non-alternant corannulene moiety within diradical systems leads to significant diradical characters as high as 0.98 for DIC-1 and 0.89 for DIC-2. Such high diradical characters can presumably be ascribed to the re-aromatization of the corannulene π system. Although the DIC compounds have large diradical characters, they display excellent stability under ambient conditions. The half-lives are 37 days for DIC-1 and 6.6 days for DIC-2 in solution. This work offers a new design strategy towards diradicaloids with large diradical characters yet maintain high stability.

Triindolo-Truxene Derivatives: Design, Synthesis, and Fine-Tuning of Electronic Properties and Molecular Assembly through Molecular Engineering.

Triindolo-truxene, a C3 -symmetric molecule with a large π-conjugated plane, has six methylene carbon atoms and three aromatic carbon atoms that can be facilely functionalized. Herein, butyl, carbonyl, cyano, and/or malononitrile groups were introduced at six methylene carbon atoms (6-, 14-, 22- or 8-, 16-, 24-positions) and/or three aromatic carbon atoms (2-, 10-, and 18-positions) of triindolo-truxene to produce eight derivatives. Their photophysical properties, electrochemical properties, and molecular assembly can be effectively modulated by substituents and substitution patterns. Incorporation of electron-deficient groups led to redshifts in both the absorption and emission of these derivatives and also lowered their HOMO and LUMO levels. Different substitution patterns resulted in the different intramolecular donor-acceptor interactions. Electron-deficient substituents at the methylene carbon atoms in the 6-, 14-, and 22-positions led to intramolecular charge transfer from the fluorene arms to the truxene core, whereas the corresponding substitutions at the methylene carbon atoms in the 8-, 16-, and 24-positions resulted in intramolecular charge transfer from the truxene core to the fluorene arms. The molecular packing in single crystals and molecular aggregation in solution are also influenced by the substituents and substitution patterns. This work provides a straightforward strategy to alter the properties of triindolo-truxene.

Diastereodivergent synthesis of bispirooxindoles via asymmetric Friedel-Crafts/aldol cascade reaction: co-catalyst effects on diastereoselective outcomes.

A combination of metal- and organo-catalysts sequentially catalyzing the Friedel-Crafts/aldol tandem reaction between 3-pyrrolyl-oxindoles and isatin-derived ß,γ-unsaturated α-ketoesters has been reported, which leads to two types of diastereomeric enantio-enriched bispirooxindoles with three quaternary stereocentres and synthetically valuable functional groups in high yields with excellent enantioselectivity and diastereoselectivity.

Pd-Catalyzed Asymmetric Dearomative Cycloaddition for Construction of Optically Active Pyrroloindoline and Cyclopentaindoline Derivatives: Access to 3a-Aminopyrroloindolines.

Asymmetric dearomative [3 + 2] cycloaddition reactions of 3-nitroindoles with vinyl aziridine and vinyl cyclopropanes have been respectively successfully developed in the presence of a chiral box/Pd(0) complex. A series of enantiomerically enriched 3a-nitro-hexahydropyrrolo[2,3-b]indole and 8b-nitrohexahydrocyclopenta[b]indole derivatives containing three contiguous chiral centers are smoothly obtained in high yields with satisfactory regio-, chemo-, and enantioselectivity. Remarkably, the synthetic utility of this process was demonstrated through direct reductive amination and functionalization of the carbon-carbon double bond of the desired products.

Radiation dose in the thyroid and the thyroid cancer risk attributable to CT scans for pediatric patients in one general hospital of China.

OBJECTIVE: To quantify the radiation dose in the thyroid attributable to different CT scans and to estimate the thyroid cancer risk in pediatric patients. METHODS: The information about pediatric patients who underwent CT scans was abstracted from the radiology information system in one general hospital between 1 January 2012 and 31 December 2012. The radiation doses were calculated using the ImPACT Patient Dosimetry Calculator and the lifetime attributable risk (LAR) of thyroid cancer incidence was estimated based on the National Academies Biologic Effects of Ionizing Radiation VII model. RESULTS: The subjects comprised 922 children, 68% were males, and received 971 CT scans. The range of typical radiation dose to the thyroid was estimated to be 0.61-0.92 mGy for paranasal sinus CT scans, 1.10-2.45 mGy for head CT scans, and 2.63-5.76 mGy for chest CT scans. The LAR of thyroid cancer were as follows: for head CT, 1.1 per 100,000 for boys and 8.7 per 100,000 for girls; for paranasal sinus CT scans, 0.4 per 100,000 for boys and 2.7 per 100,000 for girls; for chest CT scans, 2.2 per 100,000 for boys and 14.2 per 100,000 for girls. The risk of thyroid cancer was substantially higher for girls than for the boys, and from chest CT scans was higher than that from head or paransal sinus CT scans. CONCLUSIONS: Chest CT scans caused higher thyroid dose and the LAR of thyroid cancer incidence, compared with paransal sinus or head CT scans. Therefore, physicians should pay more attention to protect the thyroid when children underwent CT scans, especially chest CT scans.

Prediction of carbohydrate binding sites on protein surfaces with 3-dimensional probability density distributions of interacting atoms.

Non-covalent protein-carbohydrate interactions mediate molecular targeting in many biological processes. Prediction of non-covalent carbohydrate binding sites on protein surfaces not only provides insights into the functions of the query proteins; information on key carbohydrate-binding residues could suggest site-directed mutagenesis experiments, design therapeutics targeting carbohydrate-binding proteins, and provide guidance in engineering protein-carbohydrate interactions. In this work, we show that non-covalent carbohydrate binding sites on protein surfaces can be predicted with relatively high accuracy when the query protein structures are known. The prediction capabilities were based on a novel encoding scheme of the three-dimensional probability density maps describing the distributions of 36 non-covalent interacting atom types around protein surfaces. One machine learning model was trained for each of the 30 protein atom types. The machine learning algorithms predicted tentative carbohydrate binding sites on query proteins by recognizing the characteristic interacting atom distribution patterns specific for carbohydrate binding sites from known protein structures. The prediction results for all protein atom types were integrated into surface patches as tentative carbohydrate binding sites based on normalized prediction confidence level. The prediction capabilities of the predictors were benchmarked by a 10-fold cross validation on 497 non-redundant proteins with known carbohydrate binding sites. The predictors were further tested on an independent test set with 108 proteins. The residue-based Matthews correlation coefficient (MCC) for the independent test was 0.45, with prediction precision and sensitivity (or recall) of 0.45 and 0.49 respectively. In addition, 111 unbound carbohydrate-binding protein structures for which the structures were determined in the absence of the carbohydrate ligands were predicted with the trained predictors. The overall prediction MCC was 0.49. Independent tests on anti-carbohydrate antibodies showed that the carbohydrate antigen binding sites were predicted with comparable accuracy. These results demonstrate that the predictors are among the best in carbohydrate binding site predictions to date.

Protein-protein interaction site predictions with three-dimensional probability distributions of interacting atoms on protein surfaces.

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors.

Rationalization and design of the complementarity determining region sequences in an antibody-antigen recognition interface.

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes.

RIBRA--an error-tolerant algorithm for the NMR backbone assignment problem.

We develop an iterative relaxation algorithm called RIBRA for NMR protein backbone assignment. RIBRA applies nearest neighbor and weighted maximum independent set algorithms to solve the problem. To deal with noisy NMR spectral data, RIBRA is executed in an iterative fashion based on the quality of spectral peaks. We first produce spin system pairs using the spectral data without missing peaks, then the data group with one missing peak, and finally, the data group with two missing peaks. We test RIBRA on two real NMR datasets, hbSBD and hbLBD, and perfect BMRB data (with 902 proteins) and four synthetic BMRB data which simulate four kinds of errors. The accuracy of RIBRA on hbSBD and hbLBD are 91.4% and 83.6%, respectively. The average accuracy of RIBRA on perfect BMRB datasets is 98.28%, and 98.28%, 95.61%, 98.16%, and 96.28% on four kinds of synthetic datasets, respectively.