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 3r exhibited potent antiproliferative activities and a robust topoisomerase I (Top1) inhibitory activity. Further mechanism studies demonstrates that compound 3r 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.

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.

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.

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.

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.

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.

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.

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.

Summarizing Patients' Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models.

Automatically summarizing patients' main problems from daily progress notes using natural language processing methods helps to battle against information and cognitive overload in hospital settings and potentially assists providers with computerized diagnostic decision support. Problem list summarization requires a model to understand, abstract, and generate clinical documentation. In this work, we propose a new NLP task that aims to generate a list of problems in a patient's daily care plan using input from the provider's progress notes during hospitalization. We investigate the performance of T5 and BART, two state-of-the-art seq2seq transformer architectures, in solving this problem. We provide a corpus built on top of progress notes from publicly available electronic health record progress notes in the Medical Information Mart for Intensive Care (MIMIC)-III. T5 and BART are trained on general domain text, and we experiment with a data augmentation method and a domain adaptation pre-training method to increase exposure to medical vocabulary and knowledge. Evaluation methods include ROUGE, BERTScore, cosine similarity on sentence embedding, and F-score on medical concepts. Results show that T5 with domain adaptive pre-training achieves significant performance gains compared to a rule-based system and general domain pre-trained language models, indicating a promising direction for tackling the problem summarization task.

A scoping review of publicly available language tasks in clinical natural language processing.

OBJECTIVE: To provide a scoping review of papers on clinical natural language processing (NLP) shared tasks that use publicly available electronic health record data from a cohort of patients. MATERIALS AND METHODS: We searched 6 databases, including biomedical research and computer science literature databases. A round of title/abstract screening and full-text screening were conducted by 2 reviewers. Our method followed the PRISMA-ScR guidelines. RESULTS: A total of 35 papers with 48 clinical NLP tasks met inclusion criteria between 2007 and 2021. We categorized the tasks by the type of NLP problems, including named entity recognition, summarization, and other NLP tasks. Some tasks were introduced as potential clinical decision support applications, such as substance abuse detection, and phenotyping. We summarized the tasks by publication venue and dataset type. DISCUSSION: The breadth of clinical NLP tasks continues to grow as the field of NLP evolves with advancements in language systems. However, gaps exist with divergent interests between the general domain NLP community and the clinical informatics community for task motivation and design, and in generalizability of the data sources. We also identified issues in data preparation. CONCLUSION: The existing clinical NLP tasks cover a wide range of topics and the field is expected to grow and attract more attention from both general domain NLP and clinical informatics community. We encourage future work to incorporate multidisciplinary collaboration, reporting transparency, and standardization in data preparation. We provide a listing of all the shared task papers and datasets from this review in a GitLab repository.

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.

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.

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.

Adaptive estimation of continuous gait phase based on capacitive sensors.

Continuous gait phase plays an important role in robotic prosthesis control. In this paper, we have conducted the offline adaptive estimation (at different speeds and on different ramps) of continuous gait phase of robotic transtibial prosthesis based on the adaptive oscillators. We have used the capacitive sensing method to record the deformation of the muscles. Two transtibial amputees joined in this study. Based on the strain signals of the prosthetic foot and the capacitive signals of the residual limb, the maximum and minimum of estimation errors are 0.80 rad and 0.054 rad, respectively, and their corresponding ratios in one gait cycle are 1.27% and 0.86%, respectively. This paper proposes an effective method to estimate the continuous gait phase based on the capacitive signals of the residual muscles, which provides a basis for the continuous control of robotic transtibial prosthesis.

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.

Unraveling Passivation Mechanism of Imidazolium-Based Ionic Liquids on Inorganic Perovskite to Achieve Near-Record-Efficiency CsPbI2Br Solar Cells.

The application of ionic liquids in perovskite has attracted wide-spread attention for its astounding performance improvement of perovskite solar cells (PSCs). However, the detailed mechanisms behind the improvement remain mysterious. Herein, a series of imidazolium-based ionic liquids (IILs) with different cations and anions is systematically investigated to elucidate the passivation mechanism of IILs on inorganic perovskites. It is found that IILs display the following advantages: (1) They form ionic bonds with Cs+ and Pb2+ cations on the surface and at the grain boundaries of perovskite films, which could effectively heal/reduce the Cs+/I- vacancies and Pb-related defects; (2) They serve as a bridge between the perovskite and the hole-transport-layer for effective charge extraction and transfer; and (3) They increase the hydrophobicity of the perovskite surface to further improve the stability of the CsPbI2Br PSCs. The combination of the above effects results in suppressed non-radiative recombination loss in CsPbI2Br PSCs and an impressive power conversion efficiency of 17.02%. Additionally, the CsPbI2Br PSCs with IILs surface modification exhibited improved ambient and light illumination stability. Our results provide guidance for an in-depth understanding of the passivation mechanism of IILs in inorganic perovskites.

Mechanical properties and clamping behaviors of snow crab claw.

The high-performing biomimetic behaviors of crustaceans are the optimal results of long-time wise adaption to their living environment. One outstanding prototype is crab claw, which has the combining advantages of lightweight and high strength. To promote relevant engineering applications, it is imperative to explore its mechanical behaviors and structural characteristics. In this work, mechanical test and finite element analysis (FEA) are performed to reveal the fundamental mechanical properties and clamping behaviors of snow crab (Chionoecetes opilio) claw, respectively. A lightweight modeling method, parametric lofting modeling, for the 3D modeling of the claw is employed, which is compared with the traditional reverse engineering modeling method based on tomography image. Our results demonstrated that the hardness and modulus of the regions near the top of the claw are larger than those of the regions near of bottom of the claw. Moisture is a critical factor in controlling the tensile behavior of the claw and the wet specimens exhibit higher modulus and strength under tensile loading. Besides, The parametric lofting method is highly flexible and efficient in generating 3D geometrical model. The investigation of clamping behaviors provides not only insights into mechanical behaviors and intrinsic mechanisms but also a practical guide for their potential applications, such as designing high-performing artificial clamping muscles for clinical operations, aerospace applications, and robotics.