Magnetically Actuated Trigger Transient Soft Actuators Comprising On-Demand Photo-Initiated and Thermo-Degradable Polypropylene Carbonate-Photo-Acid Generator.

Lifetime-reconfigurable soft robots have emerged as a new class of robots, emphasizing the unmet needs of futuristic sustainability and security. Trigger-transient materials that can both actuate and degrade on-demand are crucial for achieving life-reconfigurable soft robots. Here, we propose the use of transient and magnetically actuating materials that can decompose under ultraviolet light and heat, achieved by adding photo-acid generator (PAG) and magnetic particles (Sr-ferrite) to poly(propylene carbonate) (PPC). Chemical and thermal analyses reveal that the mechanism of PPC-PAG decomposition occurs through PPC backbone cleavage by the photo-induced acid. The self-assembled monolayer (SAM) encapsulation of Sr-ferrite preventing the interaction with the PAG allowed the transience of magnetic soft actuators. We demonstrate remotely controllable and degradable magnetic soft kirigami actuators using blocks with various magnetized directions. This study proposes novel approaches for fabricating lifetime-configurable magnetic soft actuators applicable to diverse environments and applications, such as enclosed/sealed spaces and security/military devices.

Discovery of thiophen-2-ylmethylene bis-dimedone derivatives as novel WRN inhibitors for treating cancers with microsatellite instability.

Microsatellite instability (MSI) is a hypermutable condition caused by DNA mismatch repair system defects, contributing to the development of various cancer types. Recent research has identified Werner syndrome ATP-dependent helicase (WRN) as a promising synthetic lethal target for MSI cancers. Herein, we report the first discovery of thiophen-2-ylmethylene bis-dimedone derivatives as novel WRN inhibitors for MSI cancer therapy. Initial computational analysis and biological evaluation identified a new scaffold for a WRN inhibitor. Subsequent SAR study led to the discovery of a highly potent WRN inhibitor. Furthermore, we demonstrated that the optimal compound induced DNA damage and apoptotic cell death in MSI cancer cells by inhibiting WRN. This study provides a new pharmacophore for WRN inhibitors, emphasizing their therapeutic potential for MSI cancers.

Aß dissociation by pectolinarin may counteract against Aß-induced synaptic dysfunction and memory impairment.

Alzheimer's disease (AD) is a degenerative brain disorder characterised by various neurological symptoms, including memory impairment and mood disorders, associated with the abnormal accumulation of amyloid b(Aß) and tau proteins in the brain. There is still no definitive treatment available for AD, and the Aß antibody drugs, which are expected to be approved by the FDA, have many limitations. Therefore, there is an urgent need to develop low-molecular-weight therapeutic agents for the management of AD. In this study, we investigated whether pectolinarin, a flavonoid, regulates Aß aggregation and Aß-induced toxicity. Pectolinarin demonstrated concentration-dependent inhibition of Aß aggregation and had the ability to break down pre-formed Aß aggregates, thereby reducing their neurotoxicity. Furthermore, pectolinarin suppressed Aß aggregates-induced reduction in long-term potentiation (LTP) in the hippocampus. Oral administration of pectolinarin in experimental animals inhibited memory impairment and LTP deficits induced by Aß injection in the hippocampus. These results indicate that pectolinarin may reduce toxic Aß species and Aß-induced memory impairments and synaptic dysfunction.

Lifetime-configurable soft robots via photodegradable silicone elastomer composites.

Developing soft robots that can control their own life cycle and degrade on-demand while maintaining hyperelasticity is a notable research challenge. On-demand degradable soft robots, which conserve their original functionality during operation and rapidly degrade under specific external stimulation, present the opportunity to self-direct the disappearance of temporary robots. This study proposes soft robots and materials that exhibit excellent mechanical stretchability and can degrade under ultraviolet light by mixing a fluoride-generating diphenyliodonium hexafluorophosphate with a silicone resin. Spectroscopic analysis revealed the mechanism of Si─O─Si backbone cleavage using fluoride ion (F-) and thermal analysis indicated accelerated decomposition at elevated temperatures. In addition, we demonstrated a robotics application by fabricating electronics integrated gaiting robot and a fully closed-loop trigger disintegration robot for autonomous, application-oriented functionalities. This study provides a simple yet novel strategy for designing life cycle mimicking soft robotics that can be applied to reduce soft robotics waste, explore hazardous areas, and ensure hardware security with on-demand destructive material platforms.

Electroceuticals for Regeneration of Long Nerve Gap Using Biodegradable Conductive Conduits and Implantable Wireless Stimulator.

Regeneration of over 10 mm long peripheral nerve defects remains a challenge due to the failure of regeneration by prolonged axotomy and denervation occurring in long-term recovery. Recent studies reveal that conductive conduits and electrical stimulation accelerate the regeneration of long nerve defects. In this study, an electroceutical platform combining a fully biodegradable conductive nerve conduit and a wireless electrical stimulator is proposed to maximize the therapeutic effect on nerve regeneration. Fully biodegradable nerve conduit fabricated using molybdenum (Mo) microparticles and polycaprolactone (PCL) can eliminate the unwanted effects of non-degradable implants, which occupy nerve paths and need to be removed through surgery increasing the risk of complications. The electrical and mechanical properties of Mo/PCL conduits are optimized by controlling the amounts of Mo and tetraglycol lubricant. The dissolution behavior and electrical conductivity of biodegradable nerve conduits in the biomimetic solutions are also evaluated. In in vivo experiments, the integrated strategy of a conductive Mo/PCL conduit with controlled therapeutic electrical stimulation shows accelerated axon regeneration for long sciatic nerve defects in rats compared to the use of the Mo/PCL conduit without stimulation and has a significant therapeutic effect based on the results obtained from the functional recovery test.

Improving the quality of chemical language model outcomes with atom-in-SMILES tokenization.

Tokenization is an important preprocessing step in natural language processing that may have a significant influence on prediction quality. This research showed that the traditional SMILES tokenization has a certain limitation that results in tokens failing to reflect the true nature of molecules. To address this issue, we developed the atom-in-SMILES tokenization scheme that eliminates ambiguities in the generic nature of SMILES tokens. Our results in multiple chemical translation and molecular property prediction tasks demonstrate that proper tokenization has a significant impact on prediction quality. In terms of prediction accuracy and token degeneration, atom-in-SMILES is more effective method in generating higher-quality SMILES sequences from AI-based chemical models compared to other tokenization and representation schemes. We investigated the degrees of token degeneration of various schemes and analyzed their adverse effects on prediction quality. Additionally, token-level repetitions were quantified, and generated examples were incorporated for qualitative examination. We believe that the atom-in-SMILES tokenization has a great potential to be adopted by broad related scientific communities, as it provides chemically accurate, tailor-made tokens for molecular property prediction, chemical translation, and molecular generative models.

Three-Dimensionally Printed Expandable Structural Electronics Via Multi-Material Printing Room-Temperature-Vulcanizing (RTV) Silicone/Silver Flake Composite and RTV.

Three-dimensional (3D) printing has various applications in many fields, such as soft electronics, robotic systems, biomedical implants, and the recycling of thermoplastic composite materials. Three-dimensional printing, which was only previously available for prototyping, is currently evolving into a technology that can be utilized by integrating various materials into customized structures in a single step. Owing to the aforementioned advantages, multi-functional 3D objects or multi-material-designed 3D patterns can be fabricated. In this study, we designed and fabricated 3D-printed expandable structural electronics in a substrateless auxetic pattern that can be adapted to multi-dimensional deformation. The printability and electrical conductivity of a stretchable conductor (Ag-RTV composite) were optimized by incorporating a lubricant. The Ag-RTV and RTV were printed in the form of conducting voxels and frame voxels through multi-nozzle printing and were arranged in a negative Poisson's ratio pattern with a missing rib structure, to realize an expandable passive component. In addition, the expandable structural electronics were embedded in a soft actuator via one-step printing, confirming the possibility of fabricating stable interconnections in expanding deformation via a missing rib pattern.

Case report: Non-thrombotic iliac vein lesion: an unusual cause of unilateral leg swelling in a patient with endometrial carcinoma.

81-year-old female presented with subacute right lower extremity edema due to iliac vein compression by a markedly enlarged external iliac lymph node later identified as newly relapsed metastatic endometrial carcinoma. The patient underwent a full evaluation of the iliac vein lesion and cancer and had an intravenous stent placed with complete resolution of symptoms post-procedure.

Characterization of the role of Kunitz-type protease inhibitor domain in dimerization of amyloid precursor protein.

A major difference between amyloid precursor protein (APP) isoforms (APP695 and APP751) is the existence of a Kunitz type protease inhibitor (KPI) domain which has a significant impact on the homo- and hetero-dimerization of APP isoforms. However, the exact molecular mechanisms of dimer formation remain elusive. To characterize the role of the KPI domain in APP dimerization, we performed a single molecule pull down (SiMPull) assay where homo-dimerization between tethered APP molecules and soluble APP molecules was highly preferred regardless of the type of APP isoforms, while hetero-dimerization between tethered APP751 molecules and soluble APP695 molecules was limited. We further investigated the domain level APP-APP interactions using coarse-grained models with the Martini force field. Though the model initial ternary complexes (KPI-E1, KPI-KPI, KPI-E2, E1-E1, E2-E2, and E1-E2) generated using HADDOCK (HD) and AlphaFold2 (AF2), the binding free energy profiles and the binding affinities of the domain combinations were investigated via the umbrella sampling with Martini force field. Additionally, membrane-bound microenvironments at the domain level were modeled. As a result, it was revealed that the KPI domain has a stronger attractive interaction with itself than the E1 and E2 domains, as reported elsewhere. Thus, the KPI domain of APP751 may form additional attractive interactions with E1, E2 and the KPI domain itself, whereas it is absent in APP695. In conclusion, we found that the APP751 homo-dimer formation is predominant than the homodimerization in APP695, which is facilitated by the presence of the KPI domain.

Magnetic boron nitride adorned with Pd nanoparticles: an efficient catalyst for the reduction of nitroarenes in aqueous media.

Hexagonal boron nitride (h-BN) is an excellent support material for nanocatalysts due to its two-dimensional (2D) architectural morphology and physicochemical stability. In this study, a chemically stable, recoverable, eco-friendly, and magnetic h-BN/Pd/Fe2O3 catalyst was prepared by a one-step calcination process, in which Pd and Fe2O3 nanoparticles (NPs) were uniformly decorated on the surface of h-BN via a typical adsorption-reduction procedure. In detail, nanosized magnetic (Pd/Fe2O3) NPs were derived from a Prussian blue analogue prototype, a well-known porous metal-organic framework, and then further surface-engineered to produce magnetic BN nanoplate-supported Pd nanocatalysts. The structural and morphological features of h-BN/Pd/Fe2O3 were investigated by spectroscopic and microscopic characterization techniques. Moreover, the h-BN nanosheets endow it with stability and appropriate chemical anchoring sites which solve the problems of inefficient reaction rate and high consumption caused by the inevitable agglomeration of precious metal NPs. Under mild reaction conditions, the developed nanostructured h-BN/Pd/Fe2O3 as the catalyst shows high yield and efficient reusability in reducing nitroarenes into the corresponding anilines using sodium borohydride (NaBH4) as a reductant.

Reconstruction of lossless molecular representations from fingerprints.

The simplified molecular-input line-entry system (SMILES) is the most prevalent molecular representation used in AI-based chemical applications. However, there are innate limitations associated with the internal structure of SMILES representations. In this context, this study exploits the resolution and robustness of unique molecular representations, i.e., SMILES and SELFIES (SELF-referencIng Embedded strings), reconstructed from a set of structural fingerprints, which are proposed and used herein as vital representational tools for chemical and natural language processing (NLP) applications. This is achieved by restoring the connectivity information lost during fingerprint transformation with high accuracy. Notably, the results reveal that seemingly irreversible molecule-to-fingerprint conversion is feasible. More specifically, four structural fingerprints, extended connectivity, topological torsion, atom pairs, and atomic environments can be used as inputs and outputs of chemical NLP applications. Therefore, this comprehensive study addresses the major limitation of structural fingerprints that precludes their use in NLP models. Our findings will facilitate the development of text- or fingerprint-based chemoinformatic models for generative and translational tasks.

Recent advances in wearable iontronic sensors for healthcare applications.

Iontronic sensors have garnered significant attention as wearable sensors due to their exceptional mechanical performance and the ability to maintain electrical performance under various mechanical stimuli. Iontronic sensors can respond to stimuli like mechanical stimuli, humidity, and temperature, which has led to exploration of their potential as versatile sensors. Here, a comprehensive review of the recent researches and developments on several types of iontronic sensors (e.g., pressure, strain, humidity, temperature, and multi-modal sensors), in terms of their sensing principles, constituent materials, and their healthcare-related applications is provided. The strategies for improving the sensing performance and environmental stability of iontronic sensors through various innovative ionic materials and structural designs are reviewed. This review also provides the healthcare applications of iontronic sensors that have gained increased feasibility and broader applicability due to the improved sensing performance. Lastly, outlook section discusses the current challenges and the future direction in terms of the applicability of the iontronic sensors to the healthcare.

Economic burden of brain metastases in non-small cell lung cancer patients in South Korea: A retrospective cohort study using nationwide claims data.

Brain metastases (BM) are common in patients with non-small cell lung cancer (NSCLC). However, the pure economic burden of BM is unknown. This study aimed to evaluate the impact of BM on healthcare costs and resource utilization in patients with NSCLC by comparing patients with and without BM. This was a retrospective cohort analysis of South Korean health insurance review and assessment claims data. Patients with stage IIIB or IV NSCLC were identified (March 1, 2013 to February 28, 2018). We compared their two-year and per-patient-per-month (PPPM) healthcare costs and resource utilization with 1:3 propensity score-matched patients without the condition. A generalized linear model was used to estimate the impact of BM and other covariates on healthcare costs. After propensity score matching with the 33 402 newly diagnosed cases of stage IIIB or IV NSCLC, 3435 and 10 305 patients were classified as having or not having BM, respectively. Mean healthcare costs were significantly greater in patients with BM for both the two years (US$ 44 692 vs. US$ 32 230, p < .0001) and PPPM (US$ 3510 vs. US$ 2573, p < .0001). The length of hospital stay was longer in patients with BM (79.15 vs. 69.41 days for two years, p < .0001; 7.69 vs. 6.86 days PPPM, p < .0001), and patients with BM had more outpatient visits (50.61 vs. 46.43 times for two years, p < .0001; 3.64 vs. 3.40 times PPPM costs, p < .0001). The costs of drugs, radiology/radiotherapy, and admission comprised the majority of PPPM costs and were higher in patients with BM. The generalized linear model analysis suggested that patients with BM had significantly increased healthcare costs (by 1.29-fold, 95% confidence interval 1.26-1.32). BM is a significant economic burden for patients with NSCLC. Therefore, it is important to prevent BM in patients with NSCLC to reduce their economic burden.

Meta-Analysis Comparing Drug-Coated Balloons and Percutaneous Transluminal Angioplasty for Infrapopliteal Artery Disease.

Limited data is available regarding the safety and effectiveness of drug-coated balloon (DCB) versus conventional percutaneous transluminal balloon angioplasty (PTA) in the treatment of critical limb ischemia because of infrapopliteal peripheral arterial disease. We conducted an updated meta-analysis to assess the safety and efficacy of DCB in the treatment of infrapopliteal disease. A database search of PubMed/MEDLINE, EMBASE, and the Cochrane Library was performed by 2 reviewers from inception through November 15, 2021. Randomized trials that compared DCB with conventional PTA in treating infrapopliteal arterial disease were included. The risk ratios (RRs) and 95% confidence intervals (CIs) were reported. A total of 9 trials were included (1,501 participants) in the study. The mean age was 71.1 ± 10.2 years. Regarding the primary end points, treating infrapopliteal arterial disease with DCB had a lower incidence of re-stenosis (RR 0.48, 95% CI 0.33 to 0.70, p = 0.0001) with no significant difference in all-cause mortality (RR 1.11, 95% CI 0.73 to 1.69, p = 0.61), compared with conventional PTA. With regards to the secondary end points, DCB usage was associated with a significant reduction in clinically driven target lesion revascularization (RR 0.54, 95% CI 0.35 to 0.84, p = 0.006) with no significant difference with regards to major target limb amputation and major adverse cardiovascular events (p ≥0.05). In conclusion, among patients with critical limb ischemia secondary to infrapopliteal artery disease, DCB usage was associated with a significantly lower number of restenosis and clinically driven target lesion revascularization compared with conventional PTA. There was no increase in all-cause mortality or major target limb amputation with the use of DCB.

S-Pred: protein structural property prediction using MSA transformer.

Predicting the local structural features of a protein from its amino acid sequence helps its function prediction to be revealed and assists in three-dimensional structural modeling. As the sequence-structure gap increases, prediction methods have been developed to bridge this gap. Additionally, as the size of the structural database and computing power increase, the performance of these methods have also significantly improved. Herein, we present a powerful new tool called S-Pred, which can predict eight-state secondary structures (SS8), accessible surface areas (ASAs), and intrinsically disordered regions (IDRs) from a given sequence. For feature prediction, S-Pred uses multiple sequence alignment (MSA) of a query sequence as an input. The MSA input is converted to features by the MSA Transformer, which is a protein language model that uses an attention mechanism. A long short-term memory (LSTM) was employed to produce the final prediction. The performance of S-Pred was evaluated on several test sets, and the program consistently provided accurate predictions. The accuracy of the SS8 prediction was approximately 76%, and the Pearson's correlation between the experimental and predicted ASAs was 0.84. Additionally, an IDR could be accurately predicted with an F1-score of 0.514. The program is freely available at https://github.com/arontier/S_Pred_Paper and https://ad3.io as a code and a web server.

The discovery of penta-peptides inhibiting the activity of the formylglycine-generating enzyme and their potential antibacterial effects against Mycobacterium tuberculosis.

The formylglycine-generating enzyme is a key regulator that converts sulfatase into an active form. Despite its key role in many diseases, enzyme activity inhibitors have not yet been reported. In this study, we investigated penta-peptide ligands for FGE activity inhibition and discovered two hit peptides. In addition, the lead peptides also showed potential antibacterial effects in a Mycobacterium tuberculosis model.

Routine Invasive Strategy in Elderly Patients with Non-ST Elevation Acute Coronary Syndrome: An Updated Systematic Review and Meta-analysis of Randomized Trials.

Invasive treatment with coronary angiography is preferred approach for patients with non-ST elevation acute coronary syndrome (NSTE-ACS) compared to medical therapy alone. The results from the randomized clinical trials (RCT) that compared the invasive treatment strategy vs. conservative approach in the elderly (≥75 years) with NSTE-ACS has been inconsistent. To compare invasive and conservative strategies in the elderly (>75 years) with NSTE-ACS. We searched PubMed, Cochrane CENTRAL Register and ClinicalTrials.gov (inception through July 10, 2021) for RCTs comparing invasive and conservative strategies in the elderly with NSTE-ACS. We used random-effects model to calculate risk ratio (RR) with 95% confidence interval(CI). A total of 6 RCT including 2,323 patients were included in the meta-analysis. The median follow-up duration was 13.5 months. When invasive approach was compared to conservative strategy, it showed no difference in all-cause mortality in patients aged ≥75 years with NSTE-ACS (RR of 0.85; 95% CI 0.70-1.04; P = 0.12; I2 = 0%). There was significant reduction in MI (RR 0.59; 95% CI 0.49 0.71; P < 0.001; I2 = 0%) and unplanned revascularization (RR 0.30, 95% CI 0.17-0.53, P <0.001, I2 = 0%). Invasive strategy was associated with higher risk of major bleeding when compared to conservative treatment (RR 2.12, 95% CI 1.21-3.74, P = 0.009, I2 = 0%). Comparison of both strategies showed no significant difference in stroke (RR 0.75; 95% CI 0.38-1.46, P = 0.40; I2 = 0%). This updated meta-analysis suggests that in elderly patients (>75 years) with NSTE-ACS, a routine invasive strategy is associated with a reduction in MI and revascularization, while increasing the risk of major bleeding, but without difference in all-cause mortality and stroke.

CRFalign: A Sequence-Structure Alignment of Proteins Based on a Combination of HMM-HMM Comparison and Conditional Random Fields.

Sequence-structure alignment for protein sequences is an important task for the template-based modeling of 3D structures of proteins. Building a reliable sequence-structure alignment is a challenging problem, especially for remote homologue target proteins. We built a method of sequence-structure alignment called CRFalign, which improves upon a base alignment model based on HMM-HMM comparison by employing pairwise conditional random fields in combination with nonlinear scoring functions of structural and sequence features. Nonlinear scoring part is implemented by a set of gradient boosted regression trees. In addition to sequence profile features, various position-dependent structural features are employed including secondary structures and solvent accessibilities. Training is performed on reference alignments at superfamily levels or twilight zone chosen from the SABmark benchmark set. We found that CRFalign method produces relative improvement in terms of average alignment accuracies for validation sets of SABmark benchmark. We also tested CRFalign on 51 sequence-structure pairs involving 15 FM target domains of CASP14, where we could see that CRFalign leads to an improvement in average modeling accuracies in these hard targets (TM-CRFalign ≃42.94%) compared with that of HHalign (TM-HHalign ≃39.05%) and also that of MRFalign (TM-MRFalign ≃36.93%). CRFalign was incorporated to our template search framework called CRFpred and was tested for a random target set of 300 target proteins consisting of Easy, Medium and Hard sets which showed a reasonable template search performance.