Multi-Label Generalized Zero Shot Chest Xray Classification By Combining Image-Text Information With Feature Disentanglement.

In fully supervised learning-based medical image classification, the robustness of a trained model is influenced by its exposure to the range of candidate disease classes. Generalized Zero Shot Learning (GZSL) aims to correctly predict seen and novel unseen classes. Current GZSL approaches have focused mostly on the single-label case. However, it is common for chest X-rays to be labelled with multiple disease classes. We propose a novel multi-modal multi-label GZSL approach that leverages feature disentanglement andmulti-modal information to synthesize features of unseen classes. Disease labels are processed through a pre-trained BioBert model to obtain text embeddings that are used to create a dictionary encoding similarity among different labels. We then use disentangled features and graph aggregation to learn a second dictionary of inter-label similarities. A subsequent clustering step helps to identify representative vectors for each class. The multi-modal multi-label dictionaries and the class representative vectors are used to guide the feature synthesis step, which is the most important component of our pipeline, for generating realistic multi-label disease samples of seen and unseen classes. Our method is benchmarked against multiple competing methods and we outperform all of them based on experiments conducted on the publicly available NIH and CheXpert chest X-ray datasets.

ALFREDO: Active Learning with FeatuRe disEntangelement and DOmain adaptation for medical image classification.

State-of-the-art deep learning models often fail to generalize in the presence of distribution shifts between training (source) data and test (target) data. Domain adaptation methods are designed to address this issue using labeled samples (supervised domain adaptation) or unlabeled samples (unsupervised domain adaptation). Active learning is a method to select informative samples to obtain maximum performance from minimum annotations. Selecting informative target domain samples can improve model performance and robustness, and reduce data demands. This paper proposes a novel pipeline called ALFREDO (Active Learning with FeatuRe disEntangelement and DOmain adaptation) that performs active learning under domain shift. We propose a novel feature disentanglement approach to decompose image features into domain specific and task specific components. Domain specific components refer to those features that provide source specific information, e.g., scanners, vendors or hospitals. Task specific components are discriminative features for classification, segmentation or other tasks. Thereafter we define multiple novel cost functions that identify informative samples under domain shift. We test our proposed method for medical image classification using one histopathology dataset and two chest X-ray datasets. Experiments show our method achieves state-of-the-art results compared to other domain adaptation methods, as well as state of the art active domain adaptation methods.

Photocatalytic Proficiency of Cinnoline Moiety for Cross-Coupling Reactions: A Two in One Photocatalyst.

Herein, we have developed a new class of organic photocatalysts that can mimic transition metals for several oxidative and reductive organic cross-coupling transformations. Due to its wide potential window in both the oxidation and reduction ranges, cinnoline exhibits dual catalytic activity under visible light illumination, acting as both a photoreductant and photooxidant.

Unveiling advanced strategies for therapeutic stem cell interventions in severe burn injuries: a comprehensive review.

This comprehensive review explores the complex terrain of stem cell therapies as a potential therapeutic frontier in the healing of complicated burn wounds. Serious tissue damage, impaired healing processes, and possible long-term consequences make burn wounds a complex problem. An in-depth review is required since, despite medical progress, existing methods for treating severe burn wounds have significant limitations. Burn wounds are difficult to heal because they cause extensive tissue damage. The challenges of burn injury-induced tissue regeneration and functional recovery are also the subject of this review. Although there is a lot of promise in current stem cell treatments, there are also some limitations with scalability, finding the best way to transport the cells, and finding consistent results across different types of patients. To shed light on how to improve stem cell interventions to heal severe burn wounds, this review covers various stem cell applications in burn wounds and examines these obstacles. To overcome these obstacles, one solution is to enhance methods of stem cell distribution, modify therapies according to the severity of the burn, and conduct more studies on how stem cell therapy affects individual patients. Novel solutions may also be possible through the combination of cutting-edge technologies like nanotechnology and biotechnology. This review seeks to increase stem cell interventions by analyzing present challenges and suggesting strategic improvements. The goal is to provide a more effective and tailored way to repair serious burn wounds.

Phenalenyl-Based Photocatalyst for Bioinspired Oxidative Dehydrogenation of N-Heterocycles and Benzyl Alcohols.

The environmental benefits of molecular oxygen as the oxidizing agent in oxidation reactions that synthesize fine chemicals cannot be overstated. Increased interest in developing robust photocatalysts is stimulated by the fact that the current photocatalytic transformation boom has made previously inaccessible synthetic approaches possible. Motivated by enzymatic catalysis, employing a reusable phenalenyl-based photocatalyst, we have successfully developed oxidative dehydrogenation utilizing molecular oxygen as a greener oxidant. Under photoinduced oxidative dehydrogenation conditions, different types of saturated N-heterocycles and alcohols were successfully dehydrogenated. The versatility of this bioinspired protocol is demonstrated by the fact that a wide variety of N-heteroaromatics, such as quinoline, carbazole, quinoxaline, acridine, and indole derivatives, as well as aldehydes and ketones, were successfully synthesized. Detailed mechanistic studies validate the proposed mechanism. Fluorescence lifetime and CV experiments revealed the crucial role of water on the efficiency of the reaction. The present protocol also provides chemoselectivity and scalability, leading to superior results and allowing for the functionalization of bioactive molecules at a late stage in a sustainable manner.

Catalytic π-π Interactions Triggered Photoinduced Synthesis of Biaryls.

A highly regioselective photocatalytic method to access a variety of biaryl motifs under metal-free conditions has been developed. The organophotocatalyst is involved in π-π stacking interactions with the alkyne species, which promotes this photocatalytic process with thiophene. Mechanistic studies have shed light on these interactions and the overall process. Along with a broad functional-group tolerance and excellent regioselectivity, this protocol has been utilized in the late-stage functionalization of pharmaceuticals and other natural products.

Coordination Chemistry of Bis-Cyclic Alkyl(Amino) Carbene (cAAC)-Supported Di-Phosphorus (P2 ): An Efficient Route to Donor Base-Stabilized Elusive Di-Phosphorus-Monoxide(P2 O)-Gold Complex.

The stability and reactivity studies of heavier di-atomic group-15 congeners of alkynes, e. g., the di-phosphorus (P≡P) compounds have been the topic of huge interest because of their contrasting transient properties and lower stability compared to those of the stable molecular di-nitrogen (N≡N). Herein, we depict the reactivity studies of the bis-cAAC-stabilized di-phosphorus (P2 ) having an inversely polarized phosphaalkene nature featuring the C=P double bonds with Au(I)Cl. Both the mono-, and the di-aurated phosphaalkenes with the formulae [(Me2 -cAAC=P)2 (AuCl)] (2), and [(Me2 -cAAC=P)2 (AuCl)2 ] (3), respectively have been isolated in the solid state. Moreover, for the first time, we have been able to isolate the cAAC-stabilized tetra-aurated elusive di-phosphorus-monoxide (P2 O) with the formula [(Cy-cAAC=P)-O-(P=cAAC-Cy)(AuCl)4 ] (5) in presence of oxygen. Complexes 2-3, 5 have been structurally characterized by single crystal X-ray diffraction, and further studied by NMR spectroscopy. Our findings reveal significant elongation of the CcAAC -P bonds in 2-3, 5, and the presence of aurophilic interaction in 5. Quantum chemical calculations, including density functional theory (DFT), and energy decomposition analysis coupled with natural orbitals for chemical valence (EDA-NOCV) have been performed to study the electron densities distribution and nature of bonding in 2-3, 5.

Fruit waste: a current perspective for the sustainable production of pharmacological, nutraceutical, and bioactive resources.

Fruits are crucial components of a balanced diet and a good source of natural antioxidants, that have proven efficacy in various chronic illnesses. Various kinds of waste generated from fruit industries are considered a global concern. By utilizing this fruit waste, the international goal of "zero waste" can be achieved by sustainable utilization of these waste materials as a rich source of secondary metabolites. Moreover, to overcome this waste burden, research have focused on recovering the bioactive compounds from fruit industries and obtaining a new strategy to combat certain chronic diseases. The separation of high-value substances from fruit waste, including phytochemicals, dietary fibers, and polysaccharides which can then be used as functional ingredients for long-term health benefits. Several novel extraction technologies like ultrasound-assisted extraction (UAE), pressurized liquid extraction (PLE), and supercritical fluid extraction (SFE) could provide an alternative approach for successful extraction of the valuable bioactives from the fruit waste for their utilization as nutraceuticals, therapeutics, and value-added products. Most of these waste-derived secondary metabolites comprise polyphenols, which have been reported to have anti-inflammatory, insulin resistance-treating, cardiovascular disease-maintaining, probiotics-enhancing, or even anti-microbial and anti-viral capabilities. This review summarizes the current knowledge of fruit waste by-products in pharmacological, biological, and probiotic applications and highlights several methods for identifying efficacious bioactive compounds from fruit wastes.

Isolation of (Aryl)-(Imino) Phosphide and (Aryl)-(Phosphaalkene) Amide Complexes of Alkali Metals from Carbene-Phosphinidenes under Reductive-Thermal Rearrangements.

Invited for the cover of this issue are Sudipta Roy and co-workers at the Indian Institute of Science Education and Research (IISER) Tirupati. The image depicts the rearrangement of cyclic alkyl(amino) carbene (cAAC)-supported chloro-phosphinidenes affording two ligands, of which one was used for the solid-state isolation of three cyclic alkyl(amino-boryl) phosphaalkenes and two coinage metal clusters. Read the full text of the article at 10.1002/chem.202302120.

Skeletal rearrangement through photocatalytic denitrogenation: access to C-3 aminoquinolin-2(1H)-ones.

The addition of an amine group to a heteroaromatic system is a challenging synthetic process, yet it is an essential one in the development of many bioactive molecules. Here, we report an alternative method for the synthesis of 3-amino quinolin-2(1H)-one that overcomes the limitations of traditional methods by editing the molecular skeleton via a cascade C-N bond formation and denitrogenation process. We used TMSN3 as an aminating agent and a wide variety of 3-ylideneoxindoles as synthetic precursors for the quinolin-2(1H)-one backbone, which demonstrates remarkable tolerance of sensitive functional groups. The control experiments showed that the triazoline intermediate plays a significant role in the formation of the product. The spectroscopic investigation further defined the potential reaction pathways.

Unified Approach to Diverse Heterocyclic Synthesis: Organo-Photocatalyzed Carboacylation of Alkenes and Alkynes from Feedstock Aldehydes and Alcohols.

We report an organo-photocatalyzed carboacylation reaction that offers a springboard to create chemical complexity in a diversity-driven approach. The modular one-pot method uses feedstock aldehydes and alcohols as acyl surrogates and commercially available Eosin Y as the photoredox catalyst, making it simple and affordable to introduce structural diversity. Several biologically relevant skeletons have been easily synthesized under mild conditions in the presence of visible light irradiation by fostering a radical acylation/cyclization cascade. The proposed reaction mechanism was further illuminated by a number of spectroscopic studies. Furthermore, we applied this protocol for the late-stage functionalization of pharmaceuticals and blockbuster drugs.

Isolation of (Aryl)-(Imino) Phosphide and (Aryl)-(Phosphaalkene) Amide Complexes of Alkali Metals from Carbene-Phosphinidenes under Reductive-Thermal Rearrangements.

Two-electron reduction of cyclic alkyl(amino) carbene (cAAC)-supported chloro-phosphinidene cAAC=P-Cl (1) followed by unprecedented thermal rearrangements afforded the alkali metal complexes of (aryl)-(cyclic alkyl(imino)) phosphides 3 a-3 c, 4 a-4 b through migration of the 2,6-diisopropylphenyl (dipp) group from N to the P centre, and the (aryl)-(cyclic alkyl(phosphaalkene)) amide 5 through cleavage of the CMe2 -N bond followed by energetically favoured 5-exo-tet ring-closure in the presence of the alkali metals Cs (3 a-3 c), K (4 a, 4 b), and Li (5). Compound 3 a was found to be photoluminescent (PL), emitting bright orange light under a laboratory UV lamp of wavelength 365 nm with PL quantum yield (ϕPL ) of 2.6 % (λem =600 nm), and an average lifetime (τ) of 4.8 µs. Reaction of 3 a with CuCl and AgOTf afforded (aryl)-(cyclic alkyl(imino)) phosphide-stabilized tetra-nuclear CuI (6), and octa-nuclear AgI (7) clusters, respectively. Moreover, complexes 3 a-3 c provided a direct route for the stabilization of cyclic alkyl(aminoboryl) phosphaalkenes 8 a-8 c when treated with 1-bromo-N,N,N',N'-tetraisopropylboranediamine.

A skin lesion hair mask dataset with fine-grained annotations.

Occlusion of skin lesions in dermoscopic images due to hair affects the performance of computer-assisted lesion analysis algorithms. Lesion analysis can benefit from digital hair removal or realistic hair simulation techniques. To assist in that process, we have created the largest publicly available skin lesion hair segmentation mask dataset by carefully annotating 500 dermoscopic images. Compared to the existing datasets, our dataset is free of non-hair artifacts like ruler markers, bubbles, and ink marks. The dataset is also less prone to over and under segmentations because of fine-grained annotations and quality checks from multiple independent annotators. To create the dataset, first, we collected five hundred copyright-free CC0 licensed dermoscopic images covering different hair patterns. Second, we trained a deep learning hair segmentation model on a publicly available weakly annotated dataset. Third, we extracted hair masks for the selected five hundred images using the segmentation model. Finally, we manually corrected all the segmentation errors and verified the annotations by superimposing the annotated masks on top of the dermoscopic images. Multiple annotators were involved in the annotation and verification process to make the annotations as error-free as possible. The prepared dataset will be useful for benchmarking and training hair segmentation algorithms as well as creating realistic hair augmentation systems.

Colon Disease Diagnosis with Convolutional Neural Network and Grasshopper Optimization Algorithm.

This paper presents a robust colon cancer diagnosis method based on the feature selection method. The proposed method for colon disease diagnosis can be divided into three steps. In the first step, the images' features were extracted based on the convolutional neural network. Squeezenet, Resnet-50, AlexNet, and GoogleNet were used for the convolutional neural network. The extracted features are huge, and the number of features cannot be appropriate for training the system. For this reason, the metaheuristic method is used in the second step to reduce the number of features. This research uses the grasshopper optimization algorithm to select the best features from the feature data. Finally, using machine learning methods, colon disease diagnosis was found to be accurate and successful. Two classification methods are applied for the evaluation of the proposed method. These methods include the decision tree and the support vector machine. The sensitivity, specificity, accuracy, and F1Score have been used to evaluate the proposed method. For Squeezenet based on the support vector machine, we obtained results of 99.34%, 99.41%, 99.12%, 98.91% and 98.94% for sensitivity, specificity, accuracy, precision, and F1Score, respectively. In the end, we compared the suggested recognition method's performance to the performances of other methods, including 9-layer CNN, random forest, 7-layer CNN, and DropBlock. We demonstrated that our solution outperformed the others.

Stabilisation and reactivity studies of donor-base ligand-supported gallium-phosphides with stronger binding energy: a theoretical approach.

Gallium phosphide is a three-dimensional polymeric material of the hetero-diatomic GaP unit, which has a wurtzite type structure, and captivating application as a light emitting diode (LED). As a result, there is a constant search for suitable precursors to synthesise GaP-based materials. However, the corresponding monomeric species is exotic in nature due to the expected Ga[triple bond, length as m-dash]P multiple bond. Herein, we report on the theoretical studies of stability, chemical bonding, and reactivity of the monomeric gallium phosphides with two donor base ligands having tuneable binding energies. We have performed detailed investigations using density functional theory at three different levels (BP86/def2-TZVPP, B3LYP/def2-TZVPP, M06-2X/def2-TZVPP), QTAIM and EDA-NOCV (BP86-D3(BJ)/TZ2P, M06-2X/TZ2P) to analyse various ligand-stabilised GaP monomers, which revealed the synthetic viability of such species in the presence of stable singlet carbenes, e.g., cAAC, and NHC as ligands [cAAC = cyclic alkyl(amino) carbene, NHC = N-heterocyclic carbene] due to the larger bond dissociation energy compared to a phosphine ligand (PMe3). The calculated bond dissociation energies between a pair of ligands and the monomeric GaP unit are found to be in the range of 87 to 137 kcal mol-1, predicting their possible syntheses in the laboratory. Further, the reactivity of such species with metal carbonyls [Fe(CO)4, and Ni(CO)3] have been theoretically investigated.

Introducing Phenalenyl-Based Organic Lewis Acid as a Photocatalyst to Facilitate Oxidative Azolation of Unactivated Arenes.

By revealing the robust photooxidant properties of phenalenyl-based organic Lewis acid, we have introduced this moiety as an effective organophotocatalyst for the oxidative azolation of unactivated and feedstock arenes. In addition to its tolerance for various functional groups and scalability, this photocatalyst was shown to be promising for the defluorinative azolation of fluoroarenes.

Photoinduced Cerium-Mediated Decarboxylative Alkylation Cascade Cyclization of N-arylacrylamides and N-acryl-2-aryl benzimidazoles.

A mild and versatile cerium-mediated decarboxylative strategy for sequential alkylation/cyclization was developed for the synthesis of quaternary oxindoles and benzimidazo[2,1-a]isoquinolin-6(5H)-ones via photoinduced-LMCT. This operationally simple procedure relies on inexpensive and feedstock carboxylic acids as alkyl radical surrogates and aerial molecular oxygen as the terminal oxidant. This mild and atom economical protocol showed viability with a wide range of alkyl carboxylic acids (1° to 3° acids) as coupling partners and also allows the late-stage modification of pharmaceutically-important acids. Mechanistic studies revealed the reaction to follow radical pathway, while the decarboxylative event was studied by in situ FTIR.

Light-Induced Activation of C-X Bond via Carbonate-Assisted Anion-π Interactions: Applications to C-P and C-B Bond Formation.

We have presented a carbonate anion assisted photochemical protocol for the C-X bond activation. Anion-π interactions have been leveraged to generate aryl radicals from easily accessible aryl halides that are further utilized in C-P and C-B bond formation reactions with excellent reactivity and broad functional group tolerance. Spectroscopic investigations and DFT studies were conducted for mechanistic insights. This inexpensive method alleviates the use of a photocatalyst and the need of preactivation of the substrate for the light-induced activation of C-X bonds.

Making and Breaking of C-N Bonds: Applications in the Synthesis of Unsymmetric Tertiary Amines and α-Amino Carbonyl Derivatives.

An operationally simple process has been developed for the synthesis of unsymmetrical amines and α-amino carbonyl derivatives in the absence of a catalyst, ligand, oxidant, or any additives. Contrary to known reductive amination methods, this protocol is amenable to substrates containing other reducible groups. This process effectively results in consecutive cleavage and formation of C-N bonds. DFT studies and Hammett analysis provide useful insight into the mechanism. The role of noncovalent interactions as a stabilizing factor have been examined in the protocol. A wide range of alkyl-bromides have been coupled efficiently with a variety of dimethyl anilines to get unsymmetric tertiary amines with yields up to 90%. This methodology was further extended to the synthesis of α-amino carbonyl derivatives with yields up to 93%.