Potent and Protease Resistant Azapeptide Agonists of the GLP-1 and GIP Receptors.

The gut-derived peptide hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) play important physiological roles. Stabilized agonists of the GLP-1 receptor (GLP-1R) and the GIP receptor (GIPR) for the management of diabetes and obesity have generated widespread enthusiasm and have become blockbuster drugs. These therapeutics are refractory to the action of dipeptidyl peptidase-4 (DPP4), that catalyzes rapid removal of the two N-terminal residues of the native peptides, in turn severely diminishing their activity profiles.  Here we report that a single atom change from carbon to nitrogen in the backbone of the entire peptide make them refractory to DPP4 action while still retaining full potency and efficacy at their respective receptors.  This was accomplished by use of aza-amino acids, that are bioisosteric replacements for a-amino acids that perturb the structural backbone and local side chain conformations.  Molecular dynamics simulations reveal that aza-amino acid can populate the same conformational space that GLP-1 adopts when bound to the GLP-1R. The insertion of an aza-amino acid at the second position from the N-terminus in semaglutide and in a dual agonist of GLP-1R and GIPR further demonstrates its capability as a viable alternative to current DPP4 resistance strategies while offering additional structural variety.

ß,ß-Dimethylacrylalkannin, a key component of Zicao, induces cell cycle arrest and necrosis in hepatocellular carcinoma cells.

BACKGROUND: ß,ß-Dimethylacrylalkannin (DMAKN), a natural naphthoquinone found in Zicao, a traditional Chinese medicine (TCM), serves as the designated quantitative marker in the Chinese Pharmacopoeia. Despite its established role in assessing Zicao quality, DMAKN's biological potential remains underexplored in research. METHODS: We investigated DMAKN's involvement in Zicao's anti-hepatocellular carcinoma (HCC) properties using a combination of HPLC content analysis and comprehensive bioinformatics. Subsequently, both in vitro and in vivo experiments were conducted to evaluate DMAKN's efficacy against HCC. Mechanistic investigations focused on elucidating DMAKN's impact on cell cycle regulation and induction of cell death. RESULTS: Integrated HPLC analysis and bioinformatics identified DMAKN as the primary active compound responsible for Zicao's anti-HCC activity. In vitro and in vivo studies confirmed DMAKN's potent efficacy against HCC. Notably, DMAKN demonstrated dual effects on HCC cells: inhibiting proliferation at lower doses and inducing rapid cell death at higher doses. Mechanistic insights revealed that low-dose DMAKN induced G2/M phase cell cycle arrest through modulation of CDK1 and Cdc25C phosphorylation, while high-dose DMAKN triggered necrosis. Importantly, high-dose DMAKN caused a sharp increase in intracellular ROS levels in a short time, while low-dose DMAKN gradually increased ROS levels over a long period. Additionally, low-dose DMAKN-induced ROS activated the JNK pathway, crucial for cell cycle arrest, whereas high-dose DMAKN-induced necrosis was ROS-dependent but JNK-independent. CONCLUSION: This study underscores DMAKN's pivotal role as the principal anti-HCC compound in Zicao, delineating its differential effects and underlying mechanisms. These results demonstrate the potential of DMAKN as a therapeutic agent for the treatment of HCC, providing important information for further study and advancement in cancer therapy.

Assessing the Performance of Peptide Force Fields for Modeling the Solution Structural Ensembles of Cyclic Peptides.

Molecular dynamics simulation is a powerful tool for characterizing the solution structural ensembles of cyclic peptides. However, the ability of simulation to recapitulate experimental results and make accurate predictions largely depends on the force fields used. In our work here, we evaluate the performance of seven state-of-the-art force fields in recapitulating the experimental NMR results in water of 12 benchmark cyclic peptides, consisting of 6 cyclic pentapeptides, 4 cyclic hexapeptides, and 2 cyclic heptapeptides. The results show that RSFF2+TIP3P, RSFF2C+TIP3P, and Amber14SB+TIP3P exhibit similar and the best performance, all recapitulating the NMR-derived structure information on 10 cyclic peptides. Amber19SB+OPC successfully recapitulates the NMR-derived structure information on 8 cyclic peptides. In contrast, OPLS-AA/M+TIP4P, Amber03+TIP3P, and Amber14SBonlysc+GB-neck2 could only recapitulate the NMR-derived structure information on 5 cyclic peptides, the majority of which are not well-structured.

Investigations of In2O3 Added SiC Semiconductive Thin Films and Manufacture of a Heterojunction Diode.

This study involved direct doping of In2O3 into silicon carbide (SiC) powder, resulting in 8.0 at% In-doped SiC powder. Subsequently, heating at 500 °C was performed to form a target, followed by the utilization of electron beam (e-beam) technology to deposit the In-doped SiC thin films with the thickness of approximately 189.8 nm. The first breakthrough of this research was the successful deposition of using e-beam technology. The second breakthrough involved utilizing various tools to analyze the physical and electrical properties of In-doped SiC thin films. Hall effect measurement was used to measure the resistivity, mobility, and carrier concentration and confirm its n-type semiconductor nature. The uniform dispersion of In ions in SiC was as confirmed by electron microscopy energy-dispersive spectroscopy and secondary ion mass spectrometry analyses. The Tauc Plot method was employed to determine the Eg values of pure SiC and In-doped SiC thin films. Semiconductor parameter analyzer was used to measure the conductivity and the I-V characteristics of devices in In-doped SiC thin films. Furthermore, the third finding demonstrated that In2O3-doped SiC thin films exhibited remarkable current density. X-ray photoelectron spectroscopy and Gaussian-resolved spectra further confirmed a significant relationship between conductivity and oxygen vacancy concentration. Lastly, depositing these In-doped SiC thin films onto p-type silicon substrates etched with buffered oxide etchant resulted in the formation of heterojunction p-n junction. This junction exhibited the rectifying characteristics of a diode, with sample current values in the vicinity of 102 mA, breakdown voltage at approximately -5.23 V, and open-circuit voltage around 1.56 V. This underscores the potential of In-doped SiC thin films for various semiconductor devices.

Use of antiviral drugs and incidence of Parkinson's disease in Taiwan.

Patients infected with herpes zoster might be at risk for Parkinson's disease (PD). However, antiviral drugs may impede viral deoxyribonucleic acid (DNA) synthesis. This study aimed to determine whether the currently observed association between herpes zoster and PD is consistent with previous findings, and whether antiviral drug use is associated with PD. This retrospective cohort study used the Longitudinal Generation Tracking Database. We included patients aged 40 years and above and applied propensity score matching at 1:1 ratio for study comparability. PD risk was evaluated using Cox proportional hazards regression methods. A total of 234,730 people were analyzed. The adjusted hazard ratio (aHR) for PD in patients with herpes zoster was 1.05. Furthermore, the overall incidence of PD was lower in those treated with antiviral drugs than in the untreated ones (3.17 vs. 3.76 per 1,000 person-years); the aHR was 0.84. After stratifying for sex or age, a similar result was observed. In conclusion, herpes zoster may increase the risk of PD, particularly among females, but receiving antiviral treatment reduces the risk by 16%. Therefore, using antiviral drugs may help prevent PD. However, additional research is required to determine the underlying mechanism(s).

The immune-evasive proline-283 substitution in influenza nucleoprotein increases aggregation propensity without altering the native structure.

Nucleoprotein (NP) is a key structural protein of influenza ribonucleoprotein complexes and is central to viral RNA packing and trafficking. NP also determines the sensitivity of influenza to myxovirus resistance protein 1 (MxA), an innate immunity factor that restricts influenza replication. A few critical MxA-resistant mutations have been identified in NP, including the highly conserved proline-283 substitution. This essential proline-283 substitution impairs influenza growth, a fitness defect that becomes particularly prominent at febrile temperature (39°C) when host chaperones are depleted. Here, we biophysically characterize proline-283 NP and serine-283 NP to test whether the fitness defect is caused by the proline-283 substitution introducing folding defects. We show that the proline-283 substitution changes the folding pathway of NP, making NP more aggregation prone during folding, but does not alter the native structure of the protein. These findings suggest that influenza has evolved to hijack host chaperones to promote the folding of otherwise biophysically incompetent viral proteins that enable innate immune system escape.

Arnicolide D induces endoplasmic reticulum stress-mediated oncosis via ATF4 and CHOP in hepatocellular carcinoma cells.

Endoplasmic reticulum (ER) stress can trigger various cell death mechanisms beyond apoptosis, providing promise in cancer treatment. Oncosis, characterized by cellular swelling and increased membrane permeability, represents a non-apoptotic form of cell death. In our study, we discovered that Arnicolide D (AD), a natural sesquiterpene lactone compound, induces ER stress-mediated oncosis in hepatocellular carcinoma (HCC) cells, and this process is reactive oxygen species (ROS)-dependent. Furthermore, we identified the activation of the PERK-eIF2α-ATF4-CHOP pathway during ER stress as a pivotal factor in AD-induced oncosis. Notably, the protein synthesis inhibitor cycloheximide (CHX) was found to effectively reverse AD-induced oncosis, suggesting ATF4 and CHOP may hold crucial roles in the induction of oncosis by AD. These proteins play a vital part in promoting protein synthesis during ER stress, ultimately leading to cell death. Subsequent studies, in where we individually or simultaneously knocked down ATF4 and CHOP in HCC cells, provided further confirmation of their indispensable roles in AD-induced oncosis. Moreover, additional animal experiments not only substantiated AD's ability to inhibit HCC tumor growth but also solidified the essential role of ER stress-mediated and ROS-dependent oncosis in AD's therapeutic potential. In summary, our research findings strongly indicate that AD holds promise as a therapeutic agent for HCC by its ability to induce oncosis.

A Boron-Dependent Antibiotic Derived from a Calcium-Dependent Antibiotic.

The prevalence of drug-resistant bacterial pathogens foreshadows a healthcare crisis. Calcium-dependent antibiotics (CDAs) are promising candidates to combat infectious diseases as many of them show modes of action (MOA) orthogonal to widespread resistance mechanisms. The calcium dependence is nonetheless one of the hurdles toward realizing their full potential. Using laspartomycin C (LspC) as a model, we explored the possibility of reducing, or even eliminating, its calcium dependence. We report herein a synthetic LspC analogue (B1) whose activity no longer depends on calcium and is instead induced by phenylboronic acid (PBA). In LspC, Asp1 and Asp7 coordinate to calcium to anchor it in the active conformation; these residues are replaced by serine in B1 and condense with PBA to form a boronic ester with the same anchoring effect. Using thin-layer chromatography, MS, NMR, and complementation assays, we demonstrate that B1 inhibits bacterial growth via the same MOA as LspC, i.e., sequestering the cell wall biosynthetic intermediate undecaprenyl phosphate. B1 is as potent and effective as LspC against several Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus. Our success in converting a CDA to a boron-dependent antibiotic opens a new avenue in the design and functional control of drug molecules.

In Vitro and In Vivo Anti-Cancer Activity of Lasiokaurin in a Triple-Negative Breast Cancer Model.

Due to its intricate heterogeneity, high invasiveness, and poor prognosis, triple-negative breast cancer (TNBC) stands out as the most formidable subtype of breast cancer. At present, chemotherapy remains the prevailing treatment modality for TNBC, primarily due to its lack of estrogen receptors (ERs), progesterone receptors (PRs), and human epidermal growth receptor 2 (HER2). However, clinical chemotherapy for TNBC is marked by its limited efficacy and a pronounced incidence of adverse effects. Consequently, there is a pressing need for novel drugs to treat TNBC. Given the rich repository of diverse natural compounds in traditional Chinese medicine, identifying potential anti-TNBC agents is a viable strategy. This study investigated lasiokaurin (LAS), a natural diterpenoid abundantly present in Isodon plants, revealing its significant anti-TNBC activity both in vitro and in vivo. Notably, LAS treatment induced cell cycle arrest, apoptosis, and DNA damage in TNBC cells, while concurrently inhibiting cell metastasis. In addition, LAS effectively inhibited the activation of the phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) pathway and signal transducer and activator of transcription 3 (STAT3), thus establishing its potential for multitarget therapy against TNBC. Furthermore, LAS demonstrated its ability to reduce tumor growth in a xenograft mouse model without exerting detrimental effects on the body weight or vital organs, confirming its safe applicability for TNBC treatment. Overall, this study shows that LAS is a potent candidate for treating TNBC.

Computational Prediction of Cyclic Peptide Structural Ensembles and Application to the Design of Keap1 Binders.

The Nrf2 transcription factor is a master regulator of the cellular response to oxidative stress, and Keap1 is its primary negative regulator. Activating Nrf2 by inhibiting the Nrf2-Keap1 protein-protein interaction has shown promise for treating cancer and inflammatory diseases. A loop derived from Nrf2 has been shown to inhibit Keap1 selectively, especially when cyclized, but there are no reliable design methods for predicting an optimal macrocyclization strategy. In this work, we employed all-atom, explicit-solvent molecular dynamics simulations with enhanced sampling methods to predict the relative degree of preorganization for a series of peptides cyclized with a set of bis-thioether "staples". We then correlated these predictions to experimentally measured binding affinities for Keap1 and crystal structures of the cyclic peptides bound to Keap1. This work showcases a computational method for designing cyclic peptides by simulating and comparing their entire solution-phase ensembles, providing key insights into designing cyclic peptides as selective inhibitors of protein-protein interactions.

Reversion of chemoresistance by endocannabinoid-induced ER stress and autophagy activation in ovarian cancer.

The difficulty of detection at an early stage and the ease of developing resistance to chemotherapy render ovarian cancer (OVC) difficult to cure. Although several novel cancer therapies have been developed recently, drug resistance remains a concern since chemotherapy remains as the most commonly used treatment for cancer patients. Therefore, there is an urgent need to reclaim potential combination treatments for OVC. So far, there have been several research targeting the endocannabinoid system (ECS) in cancer. Among the various cannabinoid-based drugs, endocannabinoids, which are lipid molecules generated in the body, have been reported to produce many anti-tumor effects; however, research investigating the anti-chemoresistance effect of endocannabinoids in OVC remains unclear. In this study, we aimed to combine endocannabinoids, anandamide (AEA), and 2-arachidonoylglycerol (2-AG) with chemotherapeutic drugs as a combination approach to treat OVC. Our results showed that OVC cells expressed both cannabinoid receptors (CBR), CB1 and CB2, suggesting the possibility of endocannabinoid system (ECS) as a target. We found that the anti-chemoresistance effect mediated by endocannabinoids was caused by upregulation of ceramide levels, leading to severe endoplasmic reticulum (ER) stress and increased autophagy in chemoresistant cancer cells. Therefore, chemoresistant cancer cell growth was inhibited, and cell apoptosis was induced under combined treatments. Based on our results, endocannabinoids overcomed chemoresistance of OVC cells in vitro. Our findings suggest that drugs targeting ECS may have the potential to be adjuvants for chemotherapy by increasing the efficacy of chemotherapeutic drugs and decreasing their side effects.

Genetically encoded discovery of perfluoroaryl macrocycles that bind to albumin and exhibit extended circulation in vivo.

Peptide-based therapeutics have gained attention as promising therapeutic modalities, however, their prevalent drawback is poor circulation half-life in vivo. In this paper, we report the selection of albumin-binding macrocyclic peptides from genetically encoded libraries of peptides modified by perfluoroaryl-cysteine SNAr chemistry, with decafluoro-diphenylsulfone (DFS). Testing of the binding of the selected peptides to albumin identified SICRFFC as the lead sequence. We replaced DFS with isosteric pentafluorophenyl sulfide (PFS) and the PFS-SICRFFCGG exhibited KD = 4-6 µM towards human serum albumin. When injected in mice, the concentration of the PFS-SICRFFCGG in plasma was indistinguishable from the reference peptide, SA-21. More importantly, a conjugate of PFS-SICRFFCGG and peptide apelin-17 analogue (N3-PEG6-NMe17A2) showed retention in circulation similar to SA-21; in contrast, apelin-17 analogue was cleared from the circulation after 2 min. The PFS-SICRFFC is the smallest known peptide macrocycle with a significant affinity for human albumin and substantial in vivo circulation half-life. It is a productive starting point for future development of compact macrocycles with extended half-life in vivo.

Association between hyperlipidemia and trigger finger: A nationwide population-based cohort study.

The cause of trigger fingers remains uncertain. High lipid levels in the blood may reduce blood supply to the distal fingers and promote inflammation. We aimed to explore the association between hyperlipidemia and trigger finger. A nationwide population-based cohort study using longitudinal data from 2000 to 2013, 41,421 patients were included in the hyperlipidemia cohort and 82,842 age- and sex-matched patients were included in the control cohort. The mean age was 49.90 ± 14.73 years in the hyperlipidemia cohort and 49.79 ± 14.71 years in the control cohort. After adjusting for possible comorbidities, the hazard ratio of trigger finger in the hyperlipidemia cohort was 4.03 (95% confidence interval [CI], 3.57-4.55), with values of 4.59 (95% CI, 3.67-5.73) and 3.77 (95% CI, 3.26-4.36) among male and female patients, respectively. This large-scale population-based study demonstrated that hyperlipidemia is correlated to trigger finger.

Forensic age estimation in adults by pubic bone mineral density using multidetector computed tomography.

Radiology plays a crucial role in forensic anthropology for age estimation. However, most studies rely on morphological methods. This study aims to investigate the feasibility of using pubic bone mineral density (BMD) as a new age estimation method in the Chinese population. 468 pubic bone CT scans from living individuals in a Chinese hospital aged 18 to 87 years old were used to measure pubic BMD. The BMD of the bilateral pubic bone was measured using the Mimics software on cross-sectional CT images and the mean BMD of the bilateral pubic bone was also calculated. Regression analysis was performed to assess the correlation between pubic BMD and chronological age and to develop mathematical models for age estimation. We evaluated the accuracy of the best regression model using an independent validation sample by calculating the mean absolute error (MAE). Among all established models, the cubic regression model had the highest R2 value in both genders, with R2 = 0.550 for males and R2 = 0.634 for females. The results of the best model test showed that the MAE for predicting age using pubic BMD was 8.66 years in males and 7.69 years in females. This study highlights the potential of pubic BMD as a useful objective indicator for adult age estimation and could be used as an alternative in forensic practice when other better indicators are lacking.

Clinical outcomes in women with endometrial polyps underwent conservative management.

OBJECTIVE: To evaluate the regression rate of endometrial polyps (EPs) in a cohort of asymmetric women after conservative follow-up. MATERIALS AND METHODS: In this retrospective cohort study, a total of 1006 women with asymptomatic EPs were treated with expectant management or hormonal drugs between June 1999 and May 2018. Four hundred forty-eight women (44.5%) were administered with hormonal medications and 558 women were managed expectantly (55.5%). Office hysteroscopy was performed to confirm the diagnosis and regression of EPs. Hormonal administration included oral contraceptives, progestin and cyclic estrogen/progestin regimen according to physicians' preferences. Clinical characteristics, including the patient's age, body mass index, parity, and type of conservative management were collected. RESULTS: The mean observation time was 14.1 ± 18.5 months (range, 1-162 months). The overall regression rate of EPs in this cohort was 33.5%, 24.6% occurred after medication and 8.9% after expectant management. Patient age (<50 years) (p < 0.001), follow-up period (p = 0.005) and hormonal drugs used (p < 0.001) were significantly associated with EP regression. Twenty-four (7.1%) of the 337 EP regression patients later developed recurrent disease. Follow-up period (p < 0.001) and hormonal drugs used (p = 0.032) were closely related to polyp recurrence after initial regression. Nevertheless, multivariate logistic regression analysis revealed that hormonal drugs used was significantly associated with the regression (p < 0.001) and recurrence (p = 0.016) of EPs. CONCLUSION: Women aged 50 or less are more suitable for conservative treatment for EPs. Hormonal drugs used could increase the incidence of EP regression.

Comparison of the Degradation Effect of Methylene Blue for ZnO Nanorods Synthesized on Silicon and Indium Tin Oxide Substrates.

In the context of ZnO nanorods (NRs) grown on Si and indium tin oxide (ITO) substrates, this study aimed to compare their degradation effect on methylene blue (MB) at different concentrations. The synthesis process was carried out at a temperature of 100 °C for 3 h. After the synthesis of ZnO NRs, their crystallization was analyzed using X-ray diffraction (XRD) patterns. The XRD patterns and top-view SEM observations demonstrate variations in synthesized ZnO NRs when different substrates were used. Furthermore, cross-sectional observations reveal that ZnO NRs synthesized on an ITO substrate exhibited a slower growth rate compared to those synthesized on a Si substrate. The as-grown ZnO NRs synthesized on the Si and ITO substrates exhibited average diameters of 110 ± 40 nm and 120 ± 32 nm and average lengths of 1210 ± 55 nm and 960 ± 58 nm, respectively. The reasons behind this discrepancy are investigated and discussed. Finally, synthesized ZnO NRs on both substrates were utilized to assess their degradation effect on methylene blue (MB). Photoluminescence spectra and X-ray photoelectron spectroscopy were employed to analyze the quantities of various defects of synthesized ZnO NRs. The effect of MB degradation after 325 nm UV irradiation for different durations can be evaluated using the Beer-Lambert law, specifically by analyzing the 665 nm peak in the transmittance spectrum of MB solutions with different concentrations. Our findings reveal that ZnO NRs synthesized on an ITO substrate exhibited a higher degradation effect on MB, with a rate of 59.5%, compared to NRs synthesized on a Si substrate, which had a rate of 73.7%. The reasons behind this outcome, elucidating the factors contributing to the enhanced degradation effect are discussed and proposed.

Training Neural Network Models Using Molecular Dynamics Simulation Results to Efficiently Predict Cyclic Hexapeptide Structural Ensembles.

Cyclic peptides have emerged as a promising class of therapeutics. However, their de novo design remains challenging, and many cyclic peptide drugs are simply natural products or their derivatives. Most cyclic peptides, including the current cyclic peptide drugs, adopt multiple conformations in water. The ability to characterize cyclic peptide structural ensembles would greatly aid their rational design. In a previous pioneering study, our group demonstrated that using molecular dynamics results to train machine learning models can efficiently predict structural ensembles of cyclic pentapeptides. Using this method, which was termed StrEAMM (Structural Ensembles Achieved by Molecular Dynamics and Machine Learning), linear regression models were able to predict the structural ensembles for an independent test set with R2 = 0.94 between the predicted populations for specific structures and the observed populations in molecular dynamics simulations for cyclic pentapeptides. An underlying assumption in these StrEAMM models is that cyclic peptide structural preferences are predominantly influenced by neighboring interactions, namely, interactions between (1,2) and (1,3) residues. Here we demonstrate that for larger cyclic peptides such as cyclic hexapeptides, linear regression models including only (1,2) and (1,3) interactions fail to produce satisfactory predictions (R2 = 0.47); further inclusion of (1,4) interactions leads to moderate improvements (R2 = 0.75). We show that when using convolutional neural networks and graph neural networks to incorporate complex nonlinear interaction patterns, we can achieve R2 = 0.97 and R2 = 0.91 for cyclic pentapeptides and hexapeptides, respectively.

Deep learning enables automatic adult age estimation based on CT reconstruction images of the costal cartilage.

OBJECTIVE: Adult age estimation (AAE) is a challenging task. Deep learning (DL) could be a supportive tool. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. METHODS: Chest CT were reconstructed using volume rendering (VR) and maximum intensity projection (MIP) separately. Retrospective data of 2500 patients aged 20.00-69.99 years were obtained. The cohort was split into training (80%) and validation (20%) sets. Additional independent data from 200 patients were used as the test set and external validation set. Different modality DL models were developed accordingly. Comparisons were hierarchically performed by VR versus MIP, single-modality versus multi-modality, and DL versus manual method. Mean absolute error (MAE) was the primary parameter of comparison. RESULTS: A total of 2700 patients (mean age = 45.24 years ± 14.03 [SD]) were evaluated. Of single-modality models, MAEs yielded by VR were lower than MIP. Multi-modality models generally yielded lower MAEs than the optimal single-modality model. The best-performing multi-modality model obtained the lowest MAEs of 3.78 in males and 3.40 in females. On the test set, DL achieved MAEs of 3.78 in males and 3.92 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. For the external validation, MAEs were 6.05 in males and 6.68 in females for DL, and 6.93 and 8.28 for the manual method. CONCLUSIONS: DL demonstrated better performance than the manual method in AAE based on CT reconstruction of the costal cartilage. CLINICAL RELEVANCE STATEMENT: Aging leads to diseases, functional performance deterioration, and both physical and physiological damage over time. Accurate AAE may aid in diagnosing the personalization of aging processes. KEY POINTS: • VR-based DL models outperformed MIP-based models with lower MAEs and higher R2 values. • All multi-modality DL models showed better performance than single-modality models in adult age estimation. • DL models achieved a better performance than expert assessments.

Controlled Synthesis and Enhanced Gas Sensing Performance of Zinc-Doped Indium Oxide Nanowires.

Indium oxide (In2O3) is a widely used n-type semiconductor for detection of pollutant gases; however, its gas selectivity and sensitivity have been suboptimal in previous studies. In this work, zinc-doped indium oxide nanowires with appropriate morphologies and high crystallinity were synthesized using chemical vapor deposition (CVD). An accurate method for electrical measurement was attained using a single nanowire microdevice, showing that electrical resistivity increased after doping with zinc. This is attributed to the lower valence of the dopant, which acts as an acceptor, leading to the decrease in electrical conductivity. X-ray photoelectron spectroscopy (XPS) analysis confirms the increased oxygen vacancies due to doping a suitable number of atoms, which altered oxygen adsorption on the nanowires and contributed to improved gas sensing performance. The sensing performance was evaluated using reducing gases, including carbon monoxide, acetone, and ethanol. Overall, the response of the doped nanowires was found to be higher than that of undoped nanowires at a low concentration (5 ppm) and low operating temperatures. At 300 °C, the gas sensing response of zinc-doped In2O3 nanowires was 13 times higher than that of undoped In2O3 nanowires. The study concludes that higher zinc doping concentration in In2O3 nanowires improves gas sensing properties by increasing oxygen vacancies after doping and enhancing gas molecule adsorption. With better response to reducing gases, zinc-doped In2O3 nanowires will be applicable in environmental detection and life science.