Zirconaaziridine-Mediated Ni-Catalyzed Diastereoselective C(sp2)-Glycosylation.

In the realm of organic synthesis, the catalytic and stereoselective formation of C-glycosidic bonds is a pivotal process, bridging carbohydrates with aglycones. However, the inherent chirality of the saccharide scaffold often has a substantial impact on the stereoinduction imposed by a chiral ligand. In this study, we have established an unprecedented zirconaaziridine-mediated asymmetric nickel catalysis, enabling the diastereoselective coupling of bench-stable glycosyl phosphates with a range of (hetero)aromatic and glycal iodides as feasible coupling electrophiles. Our developed method showcases a broad scope and a high tolerance for various functional groups. More importantly, precise stereocontrol toward both anomeric configurations of forming C(sp2)-glycosides can be realized by simply utilizing the popular chiral bioxazoline (biOx) ligands in this reductive Ni catalysis. Regarding the operating mechanism, both experimental and computational studies support the occurrence of a redox transmetalation process, leading to the formation of a transient, bimetallic Ni-Zr species that acts as a potent and efficient single-electron reductant in the catalytic process.

Heuristic data-driven anchor generation for UAV-based maritime rescue image object detection.

The specificity of scenarios and tasks in Unmanned Aerial Vehicles (UAV)-based maritime rescue poses challenges for detecting targets within images captured by drones in such environments. This study focuses on leveraging heuristic methods to extract data features from specific UAV maritime rescue images to optimize the generation of anchor boxes in detection models. Experiments conducted on the large-scale SeaDronesSee maritime rescue dataset, using the MMDetection object detection framework, demonstrated that the optimized anchor boxes, improved model performance by 48.9% to 62.8% compared to the framework's default configuration, with the most proficient model surpassing the official highest SeaDronesSee baseline by over 49.3%. Further analysis of the results revealed the variation in detection difficulty for different objects within the dataset and identified the reasons behind these differences. The methodology and analysis presented in this study hold promise for optimizing UAV-based maritime rescue object detection models as well as refining data analysis and enhancement.

Copper-Catalyzed Enantioselective C(sp3 )-SCF3 Coupling of Carbon-Centered Benzyl Radicals with (Me4 N)SCF3.

In contrast with the well-established C(sp2 )-SCF3 cross-coupling to forge the Ar-SCF3 bond, the corresponding enantioselective coupling of readily available alkyl electrophiles to forge chiral C(sp3 )-SCF3 bond has remained largely unexplored. We herein disclose a copper-catalyzed enantioselective radical C(sp3 )-SCF3 coupling of a range of secondary/tertiary benzyl radicals with the easily available (Me4 N)SCF3 reagent. The key to the success lies in the utilization of chiral phosphino-oxazoline-derived anionic N,N,P-ligands through tuning electronic and steric effects for the simultaneous control of the reaction initiation and enantioselectivity. This strategy can successfully realize two types of asymmetric radical reactions, including enantioconvergent C(sp3 )-SCF3 cross-coupling of racemic benzyl halides and three-component 1,2-carbotrifluoromethylthiolation of arylated alkenes under mild reaction conditions. It therefore provides a highly flexible platform for the rapid assembly of an array of enantioenriched SCF3 -containing molecules of interest in organic synthesis and medicinal chemistry.

A general copper-catalysed enantioconvergent C(sp3)-S cross-coupling via biomimetic radical homolytic substitution.

Although α-chiral C(sp3)-S bonds are of enormous importance in organic synthesis and related areas, the transition-metal-catalysed enantioselective C(sp3)-S bond construction still represents an underdeveloped domain probably due to the difficult heterolytic metal-sulfur bond cleavage and notorious catalyst-poisoning capability of sulfur nucleophiles. Here we demonstrate the use of chiral tridentate anionic ligands in combination with Cu(I) catalysts to enable a biomimetic enantioconvergent radical C(sp3)-S cross-coupling reaction of both racemic secondary and tertiary alkyl halides with highly transformable sulfur nucleophiles. This protocol not only exhibits a broad substrate scope with high enantioselectivity but also provides universal access to a range of useful α-chiral alkyl organosulfur compounds with different sulfur oxidation states, thus providing a complementary approach to known asymmetric C(sp3)-S bond formation methods. Mechanistic results support a biomimetic radical homolytic substitution pathway for the critical C(sp3)-S bond formation step.

Kinetics of H· Transfer from CpCr(CO)3H to Various Enamides: Application to Construction of Pyrrolidines.

The rate constants kH (kD) have been determined at 27 °C for H· (D·) transfer from CpCr(CO)3H(D) to the C=C bonds of various enamides. This process leads to the formation of α-amino radicals. Vinyl enamides with N-alkyl and N-phenyl substituents have proven to be good H· acceptors, with rate constants close to those of styrene and methyl methacrylate. A methyl substituent on the incipient radical site decreases kH by a factor of 4; a methyl substituent on the carbon that will receive the H· decreases kH by a factor of 380. The measured kH values indicate that these α-amino radicals can be used for the cyclization of enamides to pyrrolidines. A vanadium hydride, HV(CO)4(dppe), has proven more effective at the cyclization of enamides than Cr or Co hydrides-presumably because the weakness of the V-H bond leads to faster H· transfer. The use of the vanadium hydride is operationally simple, employs mild reaction conditions, and has a broad substrate scope. Calculations have confirmed that H· transfer is the slowest step in these cyclization reactions.

Cu(I)-Catalyzed Chemo- and Enantioselective Desymmetrizing C-O Bond Coupling of Acyl Radicals.

Transition-metal-catalyzed enantioselective functionalization of acyl radicals has so far not been realized, probably due to their relatively high reactivity, which renders the chemo- and stereocontrol challenging. Herein, we describe Cu(I)-catalyzed enantioselective desymmetrizing C-O bond coupling of acyl radicals. This reaction is compatible with (hetero)aryl and alkyl aldehydes and, more importantly, displays a very broad scope of challenging alcohol substrates, such as 2,2-disubstituted 1,3-diols, 2-substituted-2-chloro-1,3-diols, 2-substituted 1,2,3-triols, 2-substituted serinols, and meso primary 1,4-diols, providing enantioenriched esters characterized by challenging acyclic tetrasubstituted carbon stereocenters. Partnered by one- or two-step follow-up transformations, this reaction provides a convenient and practical strategy for the rapid preparation of chiral C3 building blocks from readily available alcohols, particularly the industrially relevant glycerol. Mechanistic studies supported the proposed C-O bond coupling of acyl radicals.

Enantioconvergent Cu-catalysed N-alkylation of aliphatic amines.

Chiral amines are commonly used in the pharmaceutical and agrochemical industries1. The strong demand for unnatural chiral amines has driven the development of catalytic asymmetric methods1,2. Although the N-alkylation of aliphatic amines with alkyl halides has been widely adopted for over 100 years, catalyst poisoning and unfettered reactivity have been preventing the development of a catalyst-controlled enantioselective version3-5. Here we report the use of chiral tridentate anionic ligands to enable the copper-catalysed chemoselective and enantioconvergent N-alkylation of aliphatic amines with α-carbonyl alkyl chlorides. This method can directly convert feedstock chemicals, including ammonia and pharmaceutically relevant amines, into unnatural chiral α-amino amides under mild and robust conditions. Excellent enantioselectivity and functional-group tolerance were observed. The power of the method is demonstrated in a number of complex settings, including late-stage functionalization and in the expedited synthesis of diverse amine drug molecules. The current method indicates that multidentate anionic ligands are a general solution for overcoming transition-metal-catalyst poisoning.

Cu-catalysed enantioselective radical heteroatomic S-O cross-coupling.

The transition-metal-catalysed cross-coupling reaction has established itself as one of the most reliable and practical synthetic tools for the efficient construction of carbon-carbon/heteroatom (p-block elements other than carbon) bonds in both racemic and enantioselective manners. In contrast, development of the corresponding heteroatom-heteroatom cross-couplings has so far remained elusive, probably due to the under-investigated and often challenging heteroatom-heteroatom reductive elimination. Here we demonstrate the use of single-electron reductive elimination as a strategy for developing enantioselective S-O coupling under Cu catalysis, based on both experimental and theoretical results. The reaction manifests its synthetic potential by the ready preparation of challenging chiral alcohols featuring congested stereocentres, the expedient valorization of the biomass-derived feedstock glycerol, and the remarkable catalytic 4,6-desymmetrization of inositol. These results demonstrate the potential of enantioselective radical heteroatomic cross-coupling as a general chiral heteroatom-heteroatom formation strategy.

Leveraging Interpretable Feature Representations for Advanced Differential Diagnosis in Computational Medicine.

Diagnostic errors represent a critical issue in clinical diagnosis and treatment. In China, the rate of misdiagnosis in clinical diagnostics is approximately 27.8%. By comparison, in the United States, which boasts the most developed medical resources globally, the average rate of misdiagnosis is estimated to be 11.1%. It is estimated that annually, approximately 795,000 Americans die or suffer permanent disabilities due to diagnostic errors, a significant portion of which can be attributed to physicians' failure to make accurate clinical diagnoses based on patients' clinical presentations. Differential diagnosis, as an indispensable step in the clinical diagnostic process, plays a crucial role. Accurately excluding differential diagnoses that are similar to the patient's clinical manifestations is key to ensuring correct diagnosis and treatment. Most current research focuses on assigning accurate diagnoses for specific diseases, but studies providing reasonable differential diagnostic assistance to physicians are scarce. This study introduces a novel solution specifically designed for this scenario, employing machine learning techniques distinct from conventional approaches. We develop a differential diagnosis recommendation computation method for clinical evidence-based medicine, based on interpretable representations and a visualized computational workflow. This method allows for the utilization of historical data in modeling and recommends differential diagnoses to be considered alongside the primary diagnosis for clinicians. This is achieved by inputting the patient's clinical manifestations and presenting the analysis results through an intuitive visualization. It can assist less experienced doctors and those in areas with limited medical resources during the clinical diagnostic process. Researchers discuss the effective experimental results obtained from a subset of general medical records collected at Shengjing Hospital under the premise of ensuring data quality, security, and privacy. This discussion highlights the importance of addressing these issues for successful implementation of data-driven differential diagnosis recommendations in clinical practice. This study is of significant value to researchers and practitioners seeking to improve the efficiency and accuracy of differential diagnoses in clinical diagnostics using data analysis.

MLEE: A method for extracting object-level medical knowledge graph entities from Chinese clinical records.

As a typical knowledge-intensive industry, the medical field uses knowledge graph technology to construct causal inference calculations, such as "symptom-disease", "laboratory examination/imaging examination-disease", and "disease-treatment method". The continuous expansion of large electronic clinical records provides an opportunity to learn medical knowledge by machine learning. In this process, how to extract entities with a medical logic structure and how to make entity extraction more consistent with the logic of the text content in electronic clinical records are two issues that have become key in building a high-quality, medical knowledge graph. In this work, we describe a method for extracting medical entities using real Chinese clinical electronic clinical records. We define a computational architecture named MLEE to extract object-level entities with "object-attribute" dependencies. We conducted experiments based on randomly selected electronic clinical records of 1,000 patients from Shengjing Hospital of China Medical University to verify the effectiveness of the method.

Cobalt-Catalyzed Migration Isomerization of Dienes.

A cobalt-catalyzed multipositional isomerization of conjugated dienes has been reported for the first time using an 8-oxazoline iminoquinoline ligand. This reaction is operationally simple and atom-economical using readily available starting materials with an E/Z mixture to access disubstituted 1,3-dienes with excellent yields and good E,E stereoselectivity. The mechanism via alkene insertion of cobalt hydride species and ß-H elimination of a π-allyl cobalt intermediate is proposed on the basis of deuterium labeling and control experiments and density functional theory calculations.

Mechanism-based ligand design for copper-catalysed enantioconvergent C(sp3)-C(sp) cross-coupling of tertiary electrophiles with alkynes.

In contrast with the well-established enantioconvergent radical C(sp3)-C cross-coupling of racemic secondary alkyl electrophiles, the corresponding coupling of tertiary electrophiles to forge all-carbon quaternary stereocentres remains underexplored. The major challenge arises from the steric hindrance and the difficult enantio-differentiation of three distinct carbon substituents of prochiral tertiary radicals. Here we demonstrate a general copper-catalysed enantioconvergent C(sp3)-C(sp) cross-coupling of diverse racemic tertiary alkyl halides with terminal alkynes (87 examples). Key to the success is the rational design of chiral anionic N,N,N-ligands tailor-made for the computationally predicted outer-sphere radical group transfer pathway. This protocol provides a practical platform for the construction of chiral C(sp3)-C(sp/sp2/sp3) bonds, allowing for expedient access to an array of synthetically challenging quaternary carbon building blocks of interest in organic synthesis and related areas.

Design of Hemilabile N,N,N-Ligands in Copper-Catalyzed Enantioconvergent Radical Cross-Coupling of Benzyl/Propargyl Halides with Alkenylboronate Esters.

The enantioconvergent radical C(sp3)-C(sp2) cross-coupling of alkyl halides with alkenylboronate esters is an appealing tool in the assembly of synthetically valuable enantioenriched alkenes owing to the ready availability, low toxicity, and air/moisture stability of alkenylboronate esters. Here, we report a copper/chiral N,N,N-ligand catalytic system for the enantioconvergent cross-coupling of benzyl/propargyl halides with alkenylboronate esters (>80 examples) with good functional group tolerance. The key to the success is the rational design of hemilabile N,N,N-ligands by mounting steric hindrance at the ortho position of one coordinating quinoline ring. Thus, the newly designed ligand could not only promote the radical cross-coupling process in the tridentate form but also deliver enantiocontrol over highly reactive alkyl radicals in the bidentate form. Facile follow-up transformations highlight its potential utility in the synthesis of various enantioenriched building blocks as well as in the late-stage functionalization for drug discovery.

An Exception to the Carothers Equation Caused by the Accelerated Chain Extension in a Pd/Ag Cocatalyzed Cross Dehydrogenative Coupling Polymerization.

The Carothers equation is often used to predict the utility of a small molecule reaction in a polymerization. In this study, we present the mechanistic study of Pd/Ag cocatalyzed cross dehydrogenative coupling (CDC) polymerization to synthesize a donor-acceptor (D-A) polymer of 3,3'-dihexyl-2,2'-bithiophene and 2,2',3,3',5,5',6,6'-octafluorobiphenyl, which go counter to the Carothers equation. It is uncovered that the second chain extension cross-coupling proceeds much more efficiently than the first cross-coupling and the homocoupling side reaction (at least 1 order of magnitude faster) leading to unexpectedly low homocoupling defects and high molecular weight polymers. Kinetic analyses show that C-H bond activation is rate-determining in the first cross-coupling but not in the second cross-coupling. Based on DFT calculations, the high cross-coupling rate in the second cross-coupling was ascribed to the strong Pd-thiophene interaction in the Pd-mediated C-H bond activation transition state, which decreases the energy barrier of the Pd-mediated C-H bond activation. These results have implications beyond polymerizations and can be used to ease the synthesis of a wide range of molecules where C-H bond activation may be the limiting factor.

Asymmetric dearomatization catalysed by chiral Brønsted acids via activation of ynamides.

Chiral Brønsted acid-catalysed asymmetric synthesis has received tremendous interest over the past decades, and numerous efficient synthetic methods have been developed based on this approach. However, the use of chiral Brønsted acids in these reactions is mostly limited to the activation of imine and carbonyl moieties, and the direct activation of carbon-carbon triple bonds has so far not been invoked. Here we show that chiral Brønsted acids enable the catalytic asymmetric dearomatization reactions of naphthol-, phenol- and pyrrole-ynamides by the direct activation of alkynes. This method leads to the practical and atom-economic construction of various valuable spirocyclic enones and 2H-pyrroles that bear a chiral quaternary carbon stereocentre in generally good-to-excellent yields with excellent chemo-, regio- and enantioselectivities. The activation mode of chiral Brønsted acid catalysis revealed in this study is expected to be of broad utility in catalytic asymmetric reactions that involve ynamides and the related heteroatom-substituted alkynes.

Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging.

Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important that the WM tracts can be accurately and reproducibly characterized from brain diffusion MRI. In addition, to enable analysis of WM tracts in large datasets and in clinical practice it is essential to have methodology that is fast and easy to apply. This work therefore presents a new approach for WM tract segmentation: Neuro4Neuro, that is capable of direct extraction of WM tracts from diffusion tensor images using convolutional neural network (CNN). This 3D end-to-end method is trained to segment 25 WM tracts in aging individuals from a large population-based study (N â€‹= â€‹9752, 1.5T MRI). The proposed method showed good segmentation performance and high reproducibility, i.e., a high spatial agreement (Cohen's kappa, κ=0.72-0.83) and a low scan-rescan error in tract-specific diffusion measures (e.g., fractional anisotropy: ε=1%-5%). The reproducibility of the proposed method was higher than that of a tractography-based segmentation algorithm, while being orders of magnitude faster (0.5s to segment one tract). In addition, we showed that the method successfully generalizes to diffusion scans from an external dementia dataset (N â€‹= â€‹58, 3T MRI). In two proof-of-principle experiments, we associated WM microstructure obtained using the proposed method with age in a normal elderly population, and with disease subtypes in a dementia cohort. In concordance with the literature, results showed a widespread reduction of microstructural organization with aging and substantial group-wise microstructure differences between dementia subtypes. In conclusion, we presented a highly reproducible and fast method for WM tract segmentation that has the potential of being used in large-scale studies and clinical practice.

Breast microcalcifications detection based on fusing features with DTCWT.

BACKGROUND: Breast cancer is a common disease in women. Early detection and early treatment can reduce breast cancer mortality. Studies have shown that breast cancer microcalcifications is one of the important clinical manifestations of early breast cancer, and sometimes even the only manifestation. When the mammography image shows typical malignant microcalcification, it can be diagnosed as breast cancer without any other signs of malignancy. In the aided diagnosis of microcalcifications, it is a crucial step to automatically find and locate regions of interest containing microcalcifications. However, the existing feature extraction method for microcalcifications only extracts features in the time domain or wavelet domain, and does not completely represent all the information of the region of interest. An extraction method based on the combination of Dual-Tree Complex Wavelet Transform (DTCWT) and texture features is proposed in the paper. METHODS: First, the processing operations including denoising, enhancement, and edge detection were performed on mammograms. Sub-image segmentation is then performed. DTCWT features and texture features are extracted for each sub-image.DTCWT features are combined with texture features, and then genetic algorithm is used for feature optimization. The features are classified by the Extreme Learning Machine (ELM) to achieve rapid detection and automatic extraction of ROI with microcalcifications. The experimental results verify that the feature model proposed in this paper has the highest detection rate for ROI regions. The ROI region extracted by the proposed feature model was used as subsequent experimental data. Three different methods were used to detect the microcalcifications, including Top-hat, wavelet transform, and methods combining Top-Hat and wavelet transform. RESULTS: The method was applied to 100 mammograms from the mammograms database of women in Northeast China. In the automatic extraction of ROI, the accuracy, sensitivity, specificity, positive accuracy and negative accuracy of the proposed model combined with DTCWT were 95.92%, 96.71%, 92.20%, 93.65%, 96.33%, respectively. When the Top-hat algorithm was used for microcalcifications detection, the sensitivity reached 89.6%, and the false positive detection rate was 2.6. When the wavelet transform algorithm was used for microcalcifications detection, the sensitivity was 91.1%, and the false positive detection rate was 3.28. When the combined algorithm was used for microcalcifications detection, the sensitivity was 86.7%, and the false positive detection rate decreased to 1.35. CONCLUSIONS: The proposed model combined with DTCWT features achieves better result in the automatic extraction of ROI. Moreover, in the subsequent detection of microcalcifications based on three methods, the three methods achieved better results in sensitivity and false positive detection rate, respectively.

Carboxylate breaks the arene C-H bond via a hydrogen-atom-transfer mechanism in electrochemical cobalt catalysis.

Combined computational and experimental studies elucidated the distinctive mechanistic features of electrochemical cobalt-catalyzed C-H oxygenation. A sequential electrochemical-chemical (EC) process was identified for the formation of an amidylcobalt(iii) intermediate. The synthesis, characterization, cyclic voltammetry studies, and stoichiometric reactions of the related amidylcobalt(iii) intermediate suggested that a second on-cycle electro-oxidation occurs on the amidylcobalt(iii) species, which leads to a formal Co(iv) intermediate. This amidylcobalt(iv) intermediate is essentially a cobalt(iii) complex with one additional single electron distributed on the coordinating heteroatoms. The radical nature of the coordinating pivalate allows the formal Co(iv) intermediate to undergo a novel carboxylate-assisted HAT mechanism to cleave the arene C-H bond, and a CMD mechanism could be excluded for a Co(iii/i) catalytic scenario. The mechanistic understanding of electrochemical cobalt-catalyzed C-H bond activation highlights the multi-tasking electro-oxidation and the underexplored reaction channels in electrochemical transition metal catalysis.

A similarity measure method fusing deep feature for mammogram retrieval.

BACKGROUND: Breast cancer is one of the most important malignant tumors among women causing a serious impact on women's lives and mammography is one the most important methods for breast examination. When diagnosing the breast disease, radiologists sometimes may consult some previous diagnosis cases as a reference. But there are many previous cases and it is important to find which cases are the similar cases, which is a big project costing lots of time. Medical image retrieval can provide objective reference information for doctors to diagnose disease. The method of fusing deep features can improve the retrieval accuracy, which solves the "semantic gap" problem caused by only using content features and location features. METHODS: A similarity measure method combining deep feature for mammogram retrieval is proposed in this paper. First, the images are pre-processed to extract the low-level features, including content features and location features. Before extracting location features, registration with the standard image is performed. Then, the Convolutional Neural Network, the Stacked Auto-encoder Network, and the Deep Belief Network are built to extract the deep features, which are regarded as high-level features. Next, content similarity and deep similarity are calculated separately using the Euclidean distance between the query image and the dataset images. The location similarity is obtained by calculating the ratio of intersection to union of the mass regions. Finally, content similarity, location similarity, and deep similarity are fused to form the image fusion similarity. According to the similarity, the specified number of the most similar images can be returned. RESULTS: In the experiment, 740 MLO mammograms are used, which are from women in Northeast China. The content similarity, location similarity, and deep similarity are fused by different weight coefficients. When only considering low-level features, the results are better with fusing 60% content feature similarity and 40% lesion location feature similarity. On this basis, CNN deep similarity, DBN deep similarity, and SAE deep similarity are fused separately. The experiments show that when fusing 60% DBN deep feature similarity and 40% low-level feature similarity, the results have obvious advantages. At this time, the precision is 0.745, recall is 0.850, comprehensive evaluation index is 0.794. CONCLUSIONS: We propose a similarity measure method fusing deep feature, content feature, and location feature. The retrieval results show that the precision and recall of this method have obvious advantage, compared with the content-based image retrieval and location-based image retrieval.

A diquat-containing macrocyclic anion acceptor in pure water.

By taking advantage of a newly developed self-assembly approach based on oxime condensation, we successfully obtained a tetracationic macrocycle bearing two diquats in acidic aqueous media in a high yield. The ring is able to accommodate HPO42- and HCO3- in pure water.