Two-Phase Electrosynthesis of Dihydroxycoumestans: Discovery of a New Scaffold for Topoisomerase I Poison.

Coumestan represents a biologically relevant structural motif distributed in a number of natural products, and the rapid construction of related derivatives as well as the characterization of targets would accelerate lead compound discovery in medicinal chemistry. In this work, a general and scalable approach to 8,9-dihydroxycoumestans via two-electrode constant current electrolysis was developed. The application of a two-phase (aqueous/organic) system plays a crucial role for success, protecting the sensitive o-benzoquinone intermediates from over-oxidation. Based on the structurally diverse products, a primary SAR study on coumestan scaffold was completed, and compound 3 r exhibited potent antiproliferative activities and a robust topoisomerase I (Top1) inhibitory activity. Further mechanism studies demonstrates that compound 3 r was a novel Top1 poison, which might open an avenue for the development of Top1-targeted antitumor agent.

Glycol Monomethyl Ether-Substituted Carbazolyl Hole-Transporting Material for Stable Inverted Perovskite Solar Cells with Efficiency of 25.52.

Organic self-assembled molecules (OSAMs) based hole transporting materials play a pivotal role in achieving highly efficient and stable inverted perovskite solar cells (IPSCs). However, the reported carbazol-based OSAMs have serious drawbacks, such as poor solubility in alcohol solution, worse matched energy arrangement with perovskite, and limited molecular species, which greatly limit the device performance. To address above problems, a novel OSAM 4-(3,6-glycol monomethyl ether-9H-carbazol-9-yl) butyl]phosphonic acid (GM-4PACz) was synthesized as hole-transporting material by introducing glycol monomethyl ether (GM) side chains at carbazolyl unit. GM groups enhance the surface energy of Indium Tin Oxide (ITO)/SAM substrate to facilitate the nucleation and growth of up perovskite film, suppress cation defects, release the residual stress at SAM/perovskite interface, and evaluate energy level for matching with perovskite. Consequently, the GM-4PACz based IPSC achieves a champion PCE of 25.52%, a respectable open-circuit voltage (VOC) of 1.21 V, a high stability, possessing 93.29% and 91.75% of their initial efficiency after aging in air for 2000 h or tracking at maximum power point for 1000 h, respectively.

20.67%-Efficiency Inorganic CsPbI3 Solar Cells Enabled by Zwitterion Ion Interface Treatment.

All-inorganic CsPbI3 perovskite solar cells (PSCs) have been extensively studied due to their high thermal stability and unprecedented rise in power conversion efficiency (PCE). Recently, the champion PCE of CsPbI3 PSCs has reached up to 21%; however, it is still much lower than that of organic-inorganic hybrid PSCs. Interface modification to passivate surface defects and minimize charge recombination and trapping is important to further improve the efficiency of CsPbI3 PSCs. Herein, a new zwitterion ion is deposited at the interface between electron transporting layer (ETL) and perovskite layer to passivate the defects therein. The zwitterion ions can not only passivate oxygen vacancy (VO ) and iodine vacancy (VI ) defects, but also improve the band alignment at the ETL-perovskite interface. After the interface treatment, the PCE of CsPbI3 device reaches up to 20.67%, which is among the highest values of CsPbI3 PSCs so far. Due to the defect passivation and hydrophobicity improvement, the PCE of optimized device remains 94% of its original value after 800 h storing under ambient condition. These results provide an efficient way to improve the quality of ETL-perovskite interface by zwitterion ions for achieving high performance inorganic CsPbI3 PSCs.

Crystallization Regulation by Self-Assembling Liquid Crystal Template Enables Efficient and Stable Perovskite Solar Cells.

It is found that the disordered growth of bottom perovskite film deteriorates the buried interface of perovskite solar cells (PSCs), so developing a new material to modify the buried interface for regulating the crystal growth and defect passivation is an effective approach for improving the photovoltaic performance of PSCs. Here, we developed a new ionic liquid crystal (ILC, 1-Dodecyl-3-methylimidazolium tetrafluoroborate) as both crystal regulator and defect passivator to modify the buried interface of PSCs. The high lattice matching between this ILC and perovskite promotes preferential growth of perovskite film along [001] direction, while the oriented ILC with mesomorphic phase has a strong chemical interaction with perovskite to passivate the interface defect, as a result, the modified buried interface exhibits suppressed defects, improved band alignment, reduced nonradiative recombination losses, and enhanced charge extraction. The ILC-modified PSC delivers a power conversion efficiency of 24.92 % and maintains 94 % of the original value after storage in ambient for 3000 h.

A simple neural vector space model for medical concept normalization using concept embeddings.

OBJECTIVE: Medical concept normalization (MCN), the task of linking textual mentions to concepts in an ontology, provides a solution to unify different ways of referring to the same concept. In this paper, we present a simple neural MCN model that takes mentions as input and directly predicts concepts. MATERIALS AND METHODS: We evaluate our proposed model on clinical datasets from ShARe/CLEF eHealth 2013 shared task and 2019 n2c2/OHNLP shared task track 3. Our neural MCN model consists of an encoder, and a normalized temperature-scaled softmax (NT-softmax) layer that maximizes the cosine similarity score of matching the mention to the correct concept. We adopt SAPBERT as the encoder and initialize the weights in the NT-softmax layer with pre-computed concept embeddings from SAPBERT. RESULTS: Our proposed neural model achieves competitive performance on ShARe/CLEF 2013 and establishes a new state-of-the-art on 2019-n2c2-MCN. Yet this model is simpler than most prior work: it requires no complex pipelines, no hand-crafted rules, and no preprocessing, making it simpler to apply in new settings. DISCUSSION: Analyses of our proposed model show that the NT-softmax is better than the conventional softmax on the MCN task, and both the CUI-less threshold parameter and the initialization of the weight vectors in the NT-softmax layer contribute to the improvements. CONCLUSION: We propose a simple neural model for clinical MCN, an one-step approach with simpler inference and more effective performance than prior work. Our analyses demonstrate future work on MCN may require more effort on unseen concepts.

Clinical Characteristics and Antimicrobial Susceptibility of Mycobacterium intracellulare and Mycobacterium abscessus Pulmonary Diseases: A Retrospective Study.

The incidence of nontuberculous mycobacteria (NTM) diseases is increasing every year. The present study was performed to investigate the clinical characteristics, CT findings, and drug susceptibility test (DST) results of patients diagnosed with M. intracellulare or M. abscessus nontuberculous mycobacterial pulmonary disease (NTMPD). This retrospective study included patients diagnosed with NTMPD due to M. intracellulare or M. abscessus for the first time at Anhui Chest Hospital between 01/2019 and 12/2021. The patients were grouped as M. intracellulare-NTMPD group or M. abscessus-NTMPD group. Clinical features, imaging data and DST data, were collected. Patients with M. intracellulare infection had a higher rate of acid-fast smears (66.1% vs. 45.2%, P=0.032) and a higher rate of cavitation based on pulmonary imaging (49.6% vs. 19.4%, P=0.002) than patients with M. abscessus infection, but both groups had negative TB-RNA and GeneXpert results, with no other characteristics significant differences. The results of DST showed that M. intracellulare had high susceptibility rate to moxifloxacin (95.9%), amikacin (90.1%), clarithromycin (91.7%), and rifabutin (90.1%). M. abscessus had the highest susceptibility rate to amikacin (71.0%) and clarithromycin (71.0%). The clinical features of M. intracellulare pneumopathy and M. abscessus pneumopathy are highly similar. It may be easily misdiagnosed, and therefore, early strain identification is necessary. M. intracellulare has a high susceptibility rate to moxifloxacin, amikacin, clarithromycin, and rifabutin, while M. abscessus has the highest susceptibility rate to amikacin and clarithromycin. This study provides an important clinical basis for improving the management of NTMPD.

Hydrazide Derivatives for Defect Passivation in Pure CsPbI3 Perovskite Solar Cells.

All-inorganic CsPbI3 perovskite presents preeminent chemical stability and a desirable band gap as the front absorber for perovskite/silicon tandem solar cells. Unfortunately, CsPbI3 perovskite solar cells (PSCs) still show low efficiency due to high density of defects in solution-prepared CsPbI3 films. Herein, three kinds of hydrazide derivatives (benzoyl hydrazine (BH), formohydrazide (FH) and benzamide (BA)) are designed to reduce the defect density and stabilize the phase of CsPbI3 . Calculation and characterization results corroborate that the carboxyl and hydrazine groups in BH form strong chemical bonds with Pb2+ ions, resulting in synergetic double coordination. In addition, the hydrazine group in the BH also forms a hydrogen bond with iodine to assist the coordination. Consequently, a high efficiency of 20.47 % is achieved, which is the highest PCE among all pure CsPbI3 -based PSCs reported to date. In addition, an unencapsulated device showed excellent stability in ambient air.

p-Type Carbon Dots for Effective Surface Optimization for Near-Record-Efficiency CsPbI2 Br Solar Cells.

Interface modification to minimize charge recombination and trapping for efficient charge transport is crucial for the performance of perovskite solar cells (PSCs). Herein, functionalized p-type blue carbon dots (B-CDs) are ventured as an interface passivation layer to enhance the efficiency and long-term stability of all-inorganic CsPbI2 Br PSCs. It is found that first the blue carbon dots with abundant NH, CN, CO, and CO functional groups effectively passivate defects by reacting with I- and Pb2+ ions in the perovskite through hydrogen and coordinative bonds. Second, the p-type B-CDs modifiers form a P-N junction with the n-type perovskite to provide efficient pathways for hole transfer and electron blocking. Third, the B-CDs increase the hydrophobicity of the perovskite film to improve the stability of CsPbI2 Br PSCs. With the above advantages, the CsPbI2 Br PSC with B-CDs modification shows an efficiency as high as 16.76%, one of the highest for its type. In addition, the modification renders significant improvement of air and light stability, with 95.33% of the initial PCE retained after storage in the ambient environment for 1000 h. This work demonstrates the great potential of B-CDs application in perovskite-based optoelectronic devices.

Competitive and/or cooperative interactions of graphene-family materials and benzo[a]pyrene with pulmonary surfactant: a computational and experimental study.

BACKGROUND: Airborne nanoparticles can be inhaled and deposit in human alveoli, where pulmonary surfactant (PS) molecules lining at the alveolar air-water interface act as the first barrier against inhaled nanoparticles entering the body. Although considerable efforts have been devoted to elucidate the mechanisms underlying nanoparticle-PS interactions, our understanding on this important issue is limited due to the high complexity of the atmosphere, in which nanoparticles are believed to experience transformations that remarkably change the nanoparticles' surface properties and states. By contrast with bare nanoparticles that have been extensively studied, relatively little is known about the interactions between PS and inhaled nanoparticles which already adsorb contaminants. In this combined experimental and computational effort, we investigate the joint interactions between PS and graphene-family materials (GFMs) with coexisting benzo[a]pyrene (BaP). RESULTS: Depending on the BaP concentration, molecular agglomeration, and graphene oxidation, different nanocomposite structures are formed via BaPs adsorption on GFMs. Upon deposition of GFMs carrying BaPs at the pulmonary surfactant (PS) layer, competition and cooperation of interactions between different components determines the interfacial processes including BaP solubilization, GFM translocation and PS perturbation. Importantly, BaPs adsorbed on GFMs are solubilized to increase BaP's bioavailability. By contrast with graphene adhering on the PS layer to release part of adsorbed BaPs, more BaPs are released from graphene oxide, which induces a hydrophilic pore in the PS layer and shows adverse effect on the PS biophysical function. Translocation of graphene across the PS layer is facilitated by BaP adsorption through segregating it from contact with PS, while translocation of graphene oxide is suppressed by BaP adsorption due to the increase of surface hydrophobicity. Graphene extracts PS molecules from the layer, and the resultant PS depletion declines with graphene oxidation and BaP adsorption. CONCLUSION: GFMs showed high adsorption capacity towards BaPs to form nanocomposites. Upon deposition of GFMs carrying BaPs at the alveolar air-water interface covered by a thin PS layer, the interactions of GFM-PS, GFM-BaP and BaP-PS determined the interfacial processes of BaP solubilization, GFM translocation and PS perturbation.

Expression and purification of recombinant serine protease domain of human coagulation factor XII in Pichia pastoris.

Human coagulation factor XII, the initiating factor in the intrinsic coagulation pathway, is critical for pathological thrombosis but not for hemostasis. Pharmacologic inhibition of factor XII is an attractive alternative in providing protection from pathologic thrombus formation while minimizing hemorrhagic risk. Large quantity of recombinant active factor XII is required for screening inhibitors and further research. In the present study, we designed and expressed the recombinant serine protease domain of factor XII in Pichia pastoris strain X-33, which is a eukaryotic expression model organism with low cost. The purification protocol was simplified and the protein yield was high (~20 mg/L medium). The purified serine protease domain of factor XII behaved homogeneously as a monomer, exhibited comparable activity with the human ßFXIIa, and accelerated clot formation in human plasma. This study provides the groundwork for factor XII inhibitors screening and further research.

Aminative Umpolung cyclization for synthesis of chiral exocyclic vicinal diamines.

Chiral exocylic vicinal diamines are biologically and chemically important compounds, but they are not easy to make. In this paper, an interesting aminative Umpolung cyclization process has been developed. Aromatic aldehydes 6 bearing an electrophilic chiral sulfinimine group underwent imine formation with 2,2-diphenylglycine (2), decarboxylation, and subsequent Umpolung cyclization, producing various trans-diamines 10 in 84-96% yields with high trans/cis ratios under very mild conditions. This work not only provides an efficient, clean, and mild method for the synthesis of chiral exocyclic vicinal diamines in one step but also represents a new application of aminative Umpolung strategy on intramolecular reactions.

Introducing Explorer of Taxon Concepts with a case study on spider measurement matrix building.

BACKGROUND: Taxonomic descriptions are traditionally composed in natural language and published in a format that cannot be directly used by computers. The Exploring Taxon Concepts (ETC) project has been developing a set of web-based software tools that convert morphological descriptions published in telegraphic style to character data that can be reused and repurposed. This paper introduces the first semi-automated pipeline, to our knowledge, that converts morphological descriptions into taxon-character matrices to support systematics and evolutionary biology research. We then demonstrate and evaluate the use of the ETC Input Creation - Text Capture - Matrix Generation pipeline to generate body part measurement matrices from a set of 188 spider morphological descriptions and report the findings. RESULTS: From the given set of spider taxonomic publications, two versions of input (original and normalized) were generated and used by the ETC Text Capture and ETC Matrix Generation tools. The tools produced two corresponding spider body part measurement matrices, and the matrix from the normalized input was found to be much more similar to a gold standard matrix hand-curated by the scientist co-authors. Special conventions utilized in the original descriptions (e.g., the omission of measurement units) were attributed to the lower performance of using the original input. The results show that simple normalization of the description text greatly increased the quality of the machine-generated matrix and reduced edit effort. The machine-generated matrix also helped identify issues in the gold standard matrix. CONCLUSIONS: ETC Text Capture and ETC Matrix Generation are low-barrier and effective tools for extracting measurement values from spider taxonomic descriptions and are more effective when the descriptions are self-contained. Special conventions that make the description text less self-contained challenge automated extraction of data from biodiversity descriptions and hinder the automated reuse of the published knowledge. The tools will be updated to support new requirements revealed in this case study.

Overview of the 8th Social Media Mining for Health Applications (#SMM4H) shared tasks at the AMIA 2023 Annual Symposium.

OBJECTIVE: The aim of the Social Media Mining for Health Applications (#SMM4H) shared tasks is to take a community-driven approach to address the natural language processing and machine learning challenges inherent to utilizing social media data for health informatics. In this paper, we present the annotated corpora, a technical summary of participants' systems, and the performance results. METHODS: The eighth iteration of the #SMM4H shared tasks was hosted at the AMIA 2023 Annual Symposium and consisted of 5 tasks that represented various social media platforms (Twitter and Reddit), languages (English and Spanish), methods (binary classification, multi-class classification, extraction, and normalization), and topics (COVID-19, therapies, social anxiety disorder, and adverse drug events). RESULTS: In total, 29 teams registered, representing 17 countries. In general, the top-performing systems used deep neural network architectures based on pre-trained transformer models. In particular, the top-performing systems for the classification tasks were based on single models that were pre-trained on social media corpora. CONCLUSION: To facilitate future work, the datasets-a total of 61 353 posts-will remain available by request, and the CodaLab sites will remain active for a post-evaluation phase.

Comparison of efficacies of different treatments for nontuberculous mycobacterial pulmonary disease in Anhui Province, China.

INTRODUCTION: Although nontuberculous mycobacterial (NTM) infection is a common cause of pulmonary disease worldwide, few studies have focused on epidemiological and therapeutic factors related to NTM cases in Anhui Province, China. This retrospective study aimed to identify aetiological and clinical factors, and treatment outcomes of patients with NTM pulmonary disease (NTMPD) in Anhui. METHODOLOGY: Retrospective clinical data obtained from medical records of NTMPD patients seeking care at Anhui Chest Hospital from July 2019 to June 2022 were analyzed. Treatment outcomes were compared between two patient groups: one receiving a standardised NTM treatment regimen and the other receiving precision treatment regimens. RESULTS: Genotypic analysis of 672 clinical NTMPD-associated isolates revealed that most were Mycobacterium intracellulare, while drug-susceptibility test results demonstrated diverse antibiotic resistance profiles for these isolates. Cough was the most common symptom for 101 NTMPD patients. After patients of both groups received treatment, symptoms improved, sputum culture conversion was observed for some patients, imaging findings stabilised; however, no statistically significant intergroup differences in treatment outcomes were found. CONCLUSIONS: In this study, M. intracellulare was the predominant NTM species identified in isolates obtained from NTMPD patients. Drug resistance profiles of our patient isolates were complex, highlighting the need for administration of timely, more effective, standardised treatments for patients with NTMPD in Anhui Province, China.

Dual role of pulmonary surfactant corona in modulating carbon nanotube toxicity and benzo[a]pyrene bioaccessibility.

Inhaled carbon nanotubes (CNTs) can deposit in the deep lung, where they interact with pulmonary surfactant (PS) to form coronas, potentially altering the fate and toxicity profile of CNTs. However, the presence of other contaminants in combination with CNTs may affect these interactions. Here, we used passive dosing and fluorescence-based techniques confirm the partial solubilization of BaPs adsorbed on CNTs by PS in simulated alveolar fluid. MD simulations were performed to elucidate the competition of interactions between BaPs, CNTs, and PS. We found that PS play two opposing roles in altering the toxicity profile of the CNTs. First, the formation of PS coronas reduce CNTs' toxicity by decreasing the hydrophobicity of the CNTs and decreasing their aspect ratio. Second, the interaction with PS increases the bioaccessibility of BaP through interactions with PS, which may exacerbate the inhalation toxicity of CNTs. These findings suggest that the inhalation toxicity of PS-modified CNTs should consider the bioaccessibility of coexisting contaminants, with the CNT size and aggregation state playing an important role.

25.24%-Efficiency FACsPbI3 Perovskite Solar Cells Enabled by Intermolecular Esterification Reaction of DL-Carnitine Hydrochloride.

Judicious tailoring of the interface between the SnO2 electron-transport layer and the perovskite buried surface plays a pivotal role in obtaining highly efficient and stable perovskite solar cells (PSCs). Herein, a DL-carnitine hydrochloride (DL) is incorporated into the perovskite/SnO2 interface to suppress the defect-states density. A DL-dimer is obtained at the interface by an intermolecular esterification reaction. For the SnO2 film, the Cl- in the DL-dimer can passivate oxygen vacancies (VO ) through electrostatic coupling, while the N in the DL-dimer can coordinate with the Sn4+ to passivate Sn-related defects. For the perovskite film, the DL-dimer can passivate FA+ defects via hydrogen bonding and Pb-related defects more efficiently than the DL monomer. Upon DL-dimer modification, the interfacial defects are effectively passivated and the quality of the resultant perovskite film is improved. As a result, the DL-treated device achieves a gratifying open-circuit voltage (VOC ) of 1.20 V and a champion power conversion efficiency (PCE) of 25.24%, which is a record value among all the reported FACsPbI3 PSCs to date. In addition, the unencapsulated devices exhibit a charming stability, sustaining 99.20% and 90.00% of their initial PCEs after aging in air for 1200 h and continuously operating at the maximum power point tracking for 500 h, respectively.

21.15%-Efficiency and Stable γ -CsPbI3 Perovskite Solar Cells Enabled by an Acyloin Ligand.

Cesium lead triiodide (CsPbI3 ) is a promising light-absorbing material for constructing perovskite solar cells (PSCs) owing to its favorable bandgap and thermal tolerance. However, the high density of defects in the CsPbI3 film not only act as recombination centers, but also facilitate ion migration, leading to lower PCE and inferior stability compared with the state-of-the-art organic-inorganic hybrid PSC counterpart. Theoretical analyses suggest that the effective suppression of defects in CsPbI3 film is helpful for improving the device performance. Herein, the stable and efficient γ -CsPbI3 PSCs are demonstrated by developing an acyloin ligand (1,2-di(thiophen-2-yl)ethane-1,2-dione (DED)) as a phase stabilizer and defect passivator. The experiment and calculation results confirm that carbonyl and thienyl in DED can synergistically interact with CsPbI3 by forming a chelate to effectively passivate Pb-related defects and further suppress ion migration. Consequently, DED-treated CsPbI3 PSCs yield a champion PCE of 21.15%, which is one of the highest PCE among all the reported CsPbI3 PSCs to date. In addition, the unencapsulated DED-CsPbI3 PSC can retain 94.9% of itsinitial PCE when stored under ambient conditions for 1000 h and 92.8% of its initial PCE under constant illumination for 250 h.

Overview of the 8th Social Media Mining for Health Applications (#SMM4H) Shared Tasks at the AMIA 2023 Annual Symposium.

The aim of the Social Media Mining for Health Applications (#SMM4H) shared tasks is to take a community-driven approach to address the natural language processing and machine learning challenges inherent to utilizing social media data for health informatics. The eighth iteration of the #SMM4H shared tasks was hosted at the AMIA 2023 Annual Symposium and consisted of five tasks that represented various social media platforms (Twitter and Reddit), languages (English and Spanish), methods (binary classification, multi-class classification, extraction, and normalization), and topics (COVID-19, therapies, social anxiety disorder, and adverse drug events). In total, 29 teams registered, representing 18 countries. In this paper, we present the annotated corpora, a technical summary of the systems, and the performance results. In general, the top-performing systems used deep neural network architectures based on pre-trained transformer models. In particular, the top-performing systems for the classification tasks were based on single models that were pre-trained on social media corpora. To facilitate future work, the datasets-a total of 61,353 posts-will remain available by request, and the CodaLab sites will remain active for a post-evaluation phase.

Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition.

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter user's publicly available tweets (the user's 'timeline'). In general, detecting health-related tweets is notoriously challenging for natural language processing tools. The main challenge, aside from the informality of the language used, is that people tweet about any and all topics, and most of their tweets are not related to health. Thus, finding those tweets in a user's timeline that mention specific health-related concepts such as medications requires addressing extreme imbalance. Task 3 called for detecting tweets in a user's timeline that mentions a medication name and, for each detected mention, extracting its span. The organizers made available a corpus consisting of 182 049 tweets publicly posted by 212 Twitter users with all medication mentions manually annotated. The corpus exhibits the natural distribution of positive tweets, with only 442 tweets (0.2%) mentioning a medication. This task was an opportunity for participants to evaluate methods that are robust to class imbalance beyond the simple lexical match. A total of 65 teams registered, and 16 teams submitted a system run. This study summarizes the corpus created by the organizers and the approaches taken by the participating teams for this challenge. The corpus is freely available at https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-3/. The methods and the results of the competing systems are analyzed with a focus on the approaches taken for learning from class-imbalanced data.

Meta-Learning for Decoding Neural Activity Data With Noisy Labels.

In neural decoding, a behavioral variable is often generated by manual annotation and the annotated labels could contain extensive label noise, leading to poor model generalizability. Tackling the label noise problem in neural decoding can improve model generalizability and robustness. We use a deep neural network based sample reweighting method to tackle this problem. The proposed method reweights training samples by using a small and clean validation dataset to guide learning. We evaluated the sample reweighting method on simulated neural activity data and calcium imaging data of anterior lateral motor cortex. For the simulated data, the proposed method can accurately predict the behavioral variable even in the scenario that 36 percent of samples in the training dataset are mislabeled. For the anterior lateral motor cortex study, the proposed method can predict trial types with F1 score of around 0.85 even 48 percent of training samples are mislabeled.