bluuebunny/crossref_metadata_2025 huggingface dataset:
Cervical myelopathy and extensive body destruction caused by primary Gli1 fusion sarcoma
Authors: Wang Ching‐Ying , Chu Yi‐Lin , Lin Shih‐Chieh , Wu Chih‐Chun , Huang Wen‐Cheng , Kuo Chao‐Hung
Published: November 2023

Sarcomas of the cervical spine with osteolytic lesions and intradural extension are extremely uncommon. This is a case report of a woman in her late 30s who had experienced numbness and gradual weakness of her four limbs. MRI with enhanced T1‐weighted contrast showed a heterogeneously enhancing intradural extramedullary mass lesion over C2–C4 levels compressing the spinal cord. Over the corresponding levels, the computed tomography scan showed an osteolytic lesion. Surgical intervention was performed under intraoperative neuromonitoring. Histopathological findings demonstrated a low‐grade tumor with round to ovoid nuclei with a moderate amount of eosinophilic cytoplasm with minimal nuclear pleomorphism. Next‐generation sequencing technology was employed and findings revealed PTCH1::GLI1 and GLI1::KDM2B fusion with strongly positive findings on GLI1 immunohistochemical staining. The final diagnosis was GLI1 fusion sarcoma. The patient recovered well under multidisciplinary treatment with stringent follow‐up, which are required for this rare disease entity.
Abnormal mechanical stress induced chondrocyte senescence by YAP loss‐mediated METTL3 upregulation
Authors: Yang Fan , Wang Peiqi , Dong Xiaomeng , Dai Wenyu , Chen Wanxi , Yuan Gang , Bai Ding , Xu Hui
Published: November 2023

Objectives

Abnormal mechanical stress is the pivotal risk factor of temporomandibular joint osteoarthritis (TMJOA). This study investigated the pathogenic mechanism by which abnormal mechanical stress induced chondrocyte senescence.

Materials and Methods

Cellular senescence was investigated in the rodent model of unilateral anterior crossbite and in the chondrocytes subjected to mechanical overloading in vitro. The effects of Yes‐associated protein (YAP) in chondrocyte senescence and its correlation with methyltransferase‐like 3 (METTL3) and N6‐methyladenosine (m6A) modification were evaluated. The role of m6A modification in chondrocyte senescence was determined. The therapeutic effects of m6A inhibition in TMJOA were investigated.

Results

Senescent chondrocytes were accumulated in the mechanically induced TMJOA lesions in rats and mechanical overloading could trigger chondrocyte senescence in vitro. This mechanical stress‐induced cellular senescence was revealed to be mediated by YAP deficiency that promoted METTL3‐dependent m6A modification. Moreover, inhibition of m6A modification rescued chondrocyte senescence in vitro and in vivo, and suppressed TMJOA progression in rats.

Conclusions

This study uncovered the underlying mechanism of mechanically induced senescence in TMJOA from the perspective of epitranscriptomics and revealed the therapeutic potential of m6A inhibition in TMJOA.
Site‐specific radiation dosage and implant survival in oral cancer patients: A cohort study
Authors: Alberga Jamie M. , Vissink Arjan , Korfage Anke , de Visscher Sebastiaan A. H. J. , Witjes Max J. H. , Langendijk Johannes A. , Raghoebar Gerry M.
Published: November 2023

Objectives

We assessed the radiation dosages (Dmean) on implant regions to identify the threshold for implant loss in patients with an intraoral malignancy treated with dental implants to support a mandibular denture during ablative surgery before volumetric‐modulated arc therapy (VMAT).

Materials and Methods

Data was collected prospectively from 28 patients treated surgically for an intraoral malignancy, followed by postoperative radiotherapy (VMAT) and analyzed retrospectively. Patients received 2 implants in the native mandible during ablative surgery. Implant‐specific Dmean values were retrieved from the patients' files. Radiographic bone loss was measured 1 year after implant placement and during the last follow‐up appointment. Implant survival was analyzed with the Kaplan–Meier method. Univariate logistic regression and Cox‐regression analyses were performed to investigate the effect of increasing implant‐specific radiation dosages on implant loss.

Results

Five out of 56 placed implants were lost during follow‐up (median 36.0 months, IQR 39.0). Radiographically, peri‐implant bone loss occurred in implants with a Dmean > 40 Gy. Implant loss occurred only in implants with a Dmean > 50 Gy.

Conclusion

An implant‐specific Dmean higher than 50 Gy is related to more peri‐implant bone loss and, eventually, implant loss.
MitoCur‐1 induces ferroptosis to reverse vemurafenib resistance in melanoma through inhibition of USP14
Authors: Li Gege , Zhou Changlong , Wang Lu , Zheng Yalong , Zhou Bo , Li Guoyan , Ma Zhongyu , Sun Peng , Deng Yuantao , Su Li , Wang Junling , Cui Hongmei
Published: November 2023

Melanoma is an aggressive malignant tumor with a poor prognosis. Vemurafenib (PLX4032, vem) is applied to specifically treat BRAF V600E‐mutated melanoma patients. However, prolonged usage of vem makes patients resistant to the drug and finally leads to clinical failure. We previously tested the combination regimen of tubulin inhibitor VERU‐111 with vem, as well as USP14 selective inhibitor b‐AP15 in combination with vem, both of which have showed profound therapeutic effects in overcoming vem resistance in vitro and in vivo. Most importantly, we discovered that vem‐resistant melanoma cell lines highly expressed E3 ligase SKP2 and DUB enzyme USP14, and we have demonstrated that USP14 directly interacts and stabilizes SKP2, which contributes to vem resistance. These works give us a clue that USP14 might be a promising target to overcome vem resistance in melanoma. MitoCur‐1 is a curcumin derivative, which was originally designed to specifically target tumor mitochondria inducing redox imbalance, thereby promoting tumor cell death. In this study, we have demonstrated that it can work as a novel USP14 inhibitor, and thus bears great potential in providing an anti‐tumor effect and sensitizing vem‐resistant cells by inducing ferroptosis in melanoma. Application of MitoCur‐1 dramatically induces USP14 inhibition and inactivation of GPX4 enzyme, meanwhile, increases the depletion of GSH and decreases SLC7A11 expression level. As a result, ferrous iron‐dependent lipid ROS accumulated in the cell, inducing ferroptosis, thus sensitizes the vem‐resistant melanoma cell. Interestingly, overexpression of USP14 antagonized all the ferroptosis cascade events induced by MitoCur‐1, therefore, we conclude that MitoCur‐1 induces ferroptosis through inhibition of USP14. We believe that by inhibition of USP14, vem resistance can be reversed and will finally benefit melanoma patients in future.
A novel nerve block technique for nail surgery
Authors: Park Hyoung Soo , Choi Jee Woong
Published: November 2023

In pediatric patients, nail unit anesthesia is frequently required for procedures including matrixectomy or nail avulsion. However, nail unit anesthesia is very painful and requires a significant amount of time to take complete effect, causing a great deal of distress for most pediatric patients. By targeting the palmar and dorsal digital nerves in the distal part of the fingers, our method enables fast, simple, and less painful anesthesia.
Depressed mood and perception of negative partner behavior in couple interactions: A daily diary study
Authors: Luginbuehl Tamara , Schoebi Dominik , Goh Pei Hwa , Miller John V. , Davila Joanne
Published: November 2023

Despite extensive research on depression and couple interactions, little is known about how depressed mood influences couples' experience of everyday life interactions. In this study, data were gathered from 72 different‐gender couples (N = 144 individuals), who reported their feelings, behavior, and perceptions of their partner's behavior several times a day over 14 days. The study revealed that when individuals reported feeling more depressed, they perceived their romantic partner's behavior as more distant and hurtful, and they felt treated worse and more rejected. Moreover, when individuals reported feeling more depressed, their romantic partners perceived them as more distant, and they reported feeling treated worse and more rejected. However, depressed mood did not predict subsequent relationship perceptions in time‐lagged associations, and the directionality from relationship perceptions to depressed mood was inconclusive.
The moderating role of democratic governance in the association between personal values and political ideologies
Authors: Wu Eileen Z. , Molden Daniel C.
Published: November 2023

This analysis examined whether commonly assumed associations between personal values and political attitudes within countries varied worldwide by the level of democratic governance. In less democratic countries, people may have less exposure to or engagement with value expression through political party affiliation and experience less motivation to express values through political attitudes. Therefore, in such countries, the commonly assumed association of personal values typically labeled “conservative” (e.g., tradition) or “liberal” (e.g., universalism) with right‐ or left‐wing political ideologies could be weaker. Furthermore, less democratic governments are more likely to be perceived as a deciding presence in economic outcomes than the people's or the market's will, which could alter the degree to which right‐wing economic attitudes toward free markets and private enterprise are associated with conservative values. Responses to the World Value Survey across 60 countries were largely consistent with these moderation effects when operationalizing democratic governance using both more objective, structural, and subjective, perceptual metrics. In less democratic countries, conservation‐oriented personal values were less positively associated with broad right‐wing political identification and self‐transcendence‐oriented values less positively associated with broad left‐wing political identification. In less democratic countries, conservation‐oriented values were more negatively associated with right‐wing economic attitudes.
Rapid detection of Fusarium fujikuroi in rice seeds and soaking water samples based on recombinase polymerase amplification‐lateral flow dipstick
Authors: Zhang Fuyu , Jin Chenyi , Hu Renze , Li Zhaomeng , Hu Shuodan , Zhang Yu , Zhang Chuanqing
Published: November 2023

Bakanae disease is a rice seedborne disease caused by the Fusarium (Gibberella) fujikuroi species complex (FFSC), among which F. fujikuroi is the dominant pathogen. Pathogens usually hide inside or on the surface of seeds, and infection occurs mainly at the germination stage. In this study, a method for the detection of F. fujikuroi in rice seeds and seed soaking water samples was established using recombinase polymerase amplification (RPA) technology with lateral flow device (LFD) chromatography test strips. A pair of specific primers and probes based on the cyp51c gene were screened. RPA‐LFD was used to detect 10 F. fujikuroi strains, and the results showed that all of them tested positive and there was no cross‐reaction with other Fusarium or non‐Fusarium species. The target production of the RPA‐LFD assay was obtained at 35–45°C for 8–14 min, and optimal reaction conditions of amplification at 39°C for 8 min is recommended. The sensitivity test showed that the detection limit of the RPA‐LFD test for F. fujikuroi genomic DNA in rice seeds was 100 fg/μL, and the detection limit for F. fujikuroi spores in submerged water samples was 100 spores/mL. In the assay for field samples, it successfully detected F. fujikuroi carried in the seeds of three out of five rice varieties. In addition, the whole RPA‐LFD assay can specifically detect F. fujikuroi within 30 min. This method is expected to become an early field monitoring tool for rice bakanae disease.
Overexpression of a C3HC4‐type E3‐ubiquitin ligase contributes to salinity tolerance by modulating Na+ homeostasis in rice
Authors: Kim Jong Ho , Lim Sung Don , Jung Ki‐Hong , Jang Cheol Seong
Published: November 2023

Soil salinity has a negative effect on crop yield. Therefore, plants have evolved many strategies to overcome decreases in yield under saline conditions. Among these, E3‐ubiquitin ligase regulates salt tolerance. We characterized Oryza sativa Really Interesting New Gene (RING) Finger C3HC4‐type E3 ligase (OsRFPHC‐4), which plays a positive role in improving salt tolerance. The expression of OsRFPHC‐4 was downregulated by high NaCl concentrations and induced by abscisic acid (ABA) treatment. GFP‐fused OsRFPHC‐4 was localized to the plasma membrane of rice protoplasts. OsRFPHC‐4 encodes a cellular protein with a C3HC4‐RING domain with E3 ligase activity. However, its variant OsRFPHC‐4C161A does not possess this activity. OsRFPHC‐4‐overexpressing plants showed enhanced salt tolerance due to low accumulation of Na+ in both roots and leaves, low Na+ transport in the xylem sap, high accumulation of proline and soluble sugars, high activity of reactive oxygen species (ROS) scavenging enzymes, and differential regulation of Na+/K+ transporter expression compared to wild‐type (WT) and osrfphc‐4 plants. In addition, OsRFPHC‐4‐overexpressing plants showed higher ABA sensitivity under exogenous ABA treatment than WT and osrfphc‐4 plants. Overall, these results suggest that OsRFPHC‐4 contributes to the improvement of salt tolerance and Na+/K+ homeostasis via the regulation of changes in Na+/K+ transporters.
The effect of health empowerment on elder abuse in older adults
Authors: Karaman Seda , Özer Zülfünaz , Bahçecioğlu Turan Gülcan , Yilmaz Karabulutlu Elanur
Published: November 2023

Background

Understanding elder abuse requires an assessment of variables that may limit older adults' capacities to handle their everyday lives, to live independently, and to defend themselves. This study was conducted to examine the effect of health empowerment on elder abuse in older adults.

Methods

This cross‐sectional and correlational study was conducted with 250 elderly individuals who applied to the internal medicine clinics of a university hospital in Elazig, eastern Turkey. Data were collected using the Descriptive Information Form, Elders Health Empowerment Scale (EHES) and the Hwalek‐Sengstock Elder Abuse Screening Test (H‐S/EAST).

Results

The average EHES total score of participants was 25.52 ± 6.58. The H‐S/EAST total score was 4.22 ± 3.49. Among subscales, the score of “Characteristics of the elder that make him or her vulnerable to abuse” subscale was 1.04 ± 0.83, the score of ‘Overt violation of personal rights and direct abuse’ subscale was 1.55 ± 1.30, and the score of ‘Characteristics of potentially abusive situations’ subscale was 1.62 ± 1.94. It was determined that the EHES (β = −0.163, P < 0.01) variable had a negative and significant effect on H‐S/EAST. It was found that a one‐unit decrease in the EHES variable increased the level of H‐S/EAST 0.849 times.

Conclusion

It was determined that the level of empowerment of the participants was moderate. Elderly individuals were found to have a moderate risk of elder abuse. It was found that the risk of elder abuse decreased as older individuals became stronger.
High school Black girls’ experiences in a STEM after‐school program: A qualitative case study
Authors: Allen Miranda Mullins
Published: November 2023

Due to limited research on Black girls in science education, this study focuses on the forms of capital Black girls cultivated through their participation in a community‐based STEM after‐school program. The study drew from the interviews and a focus group session of 10 Black girls and investigated their formal and informal experiences in science. Using intersectionality and community cultural wealth as theoretical perspectives, findings revealed that multiple forms of capital (aspirational, social, navigational, and familial) were fostered and interconnected throughout the program. The intersections of race and gender were also prominent contributions to the multidimensional, nuanced ways Black girls experience and flourish in STEM education. Implications and recommendations for future research on Black girls in science are discussed.
Identification of the novel HLA‐A*03:01:123 allele in a Russian individual
Authors: Ananeva Anastasiia , Sergeeva Iuliia , Andryushkina Anna V. , Shagimardanova Elena I.
Published: November 2023

Two nucleotide substitutions in exon 4 of HLA‐A*03:01:01:01 results in the novel HLA‐A*03:01:123 allele.
Weighted distances and distance transforms on the triangular tiling
Authors: Nagy Benedek
Published: November 2023

Digital geometry is a field in the intersection of discrete mathematics and geometry having various applications including geographical information systems (GIS). In digital spaces, in grids, distances can be defined based on steps in paths in somewhat similarly as in graph theory. However, the grids have more definite structures, thus one may obtain more concrete results, for example, close formulae, than on arbitrary graphs. In this article, the weighted (also called chamfer) distances, and based on them, the distance transform are investigated on the regular triangular grid. Three types of neighborhood relations are used on the grid, and therefore, three weights are used to define a distance function. Natural conditions are used on the weights such as they are positive and a larger step (in the usual and also in the Euclidean sense) cannot have a smaller weight than a smaller one. Some properties of the weighted distances are discussed; for example, they are proven to be metrics. We also give algorithms and formulae that compute the weighted distance of any point pair on a triangular grid. Algorithm for weighted distance transform is provided based on wave‐front propagation. Therefore, these new distance functions are ready for further applications in GIS, in image processing tasks, in computer vision, in graphics, in networking, and also in other applied fields.
The D‐mannose/L‐galactose pathway plays a predominant role in ascorbate biosynthesis in the liverwort Marchantia polymorpha but is not regulated by light and oxidative stress
Authors: Ishida Tetsuya , Tanaka Yasuhiro , Maruta Takanori , Ishikawa Takahiro
Published: November 2023

Ascorbate plays an indispensable role in plants, functioning as both an antioxidant and a cellular redox buffer. It is widely acknowledged that the ascorbate biosynthesis in the photosynthetic tissues of land plants is governed by light‐mediated regulation of the D‐mannose/L‐galactose (D‐Man/L‐Gal) pathway. At the core of this light‐dependent regulation lies the VTC2 gene, encoding the rate‐limiting enzyme GDP‐L‐Gal phosphorylase. The VTC2 expression is regulated by signals via the photosynthetic electron transport system. In this study, we directed our attention to the liverwort Marchantia polymorpha, representing one of the basal land plants, enabling us to conduct an in‐depth analysis of its ascorbate biosynthesis. The M. polymorpha genome harbors a solitary gene for each enzyme involved in the D‐Man/L‐Gal pathway, including VTC2, along with three lactonase orthologs, which may be involved in the alternative ascorbate biosynthesis pathway. Through supplementation experiments with potential precursors, we observed that only L‐Gal exhibited effectiveness in ascorbate biosynthesis. Furthermore, the generation of VTC2‐deficient mutants through genome editing unveiled the inability of thallus regeneration in the absence of L‐Gal supplementation, thereby revealing the importance of the D‐Man/L‐Gal pathway in ascorbate biosynthesis within M.  polymorpha. Interestingly, gene expression analyses unveiled a distinct characteristic of M. polymorpha, where none of the genes associated with the D‐Man/L‐Gal pathway, including VTC2, showed upregulation in response to light, unlike other known land plants. This study sheds light on the exceptional nature of M. polymorpha as a land plant that has evolved distinctive mechanisms concerning ascorbate biosynthesis and its regulation.
Probing the in situ volumes of Arabidopsis leaf plastids using three‐dimensional confocal and scanning electron microscopy
Authors: Knoblauch Jan , Waadt Rainer , Cousins Asaph B. , Kunz Hans‐Henning
Published: November 2023

Leaf plastids harbor a plethora of biochemical reactions including photosynthesis, one of the most important metabolic pathways on Earth. Scientists are eager to unveil the physiological processes within the organelle but also their interconnection with the rest of the plant cell. An increasingly important feature of this venture is to use experimental data in the design of metabolic models. A remaining obstacle has been the limited in situ volume information of plastids and other cell organelles. To fill this gap for chloroplasts, we established three microscopy protocols delivering in situ volumes based on: (i) chlorophyll fluorescence emerging from the thylakoid membrane, (ii) a CFP marker embedded in the envelope, and (iii) calculations from serial block‐face scanning electron microscopy (SBFSEM). The obtained data were corroborated by comparing wild‐type data with two mutant lines affected in the plastid division machinery known to produce small and large mesophyll chloroplasts, respectively. Furthermore, we also determined the volume of the much smaller guard cell plastids. Interestingly, their volume is not governed by the same components of the division machinery which defines mesophyll plastid size. Based on our three approaches, the average volume of a mature Col‐0 wild‐type mesophyll chloroplasts is 93 μm3. Wild‐type guard cell plastids are approximately 18 μm3. Lastly, our comparative analysis shows that the chlorophyll fluorescence analysis can accurately determine chloroplast volumes, providing an important tool to research groups without access to transgenic marker lines expressing genetically encoded fluorescence proteins or costly SBFSEM equipment.
Copper Extraction Using LIX 84 as a Mobile Carrier in the Emulsion Liquid Membrane Process
Authors: Kahar Izzat Naim Shamsul , Ali Ahmad Syuhaib , Othman Norasikin , Noah Norul Fatiha Mohamed , Suliman Sazmin Sufi
Published: November 2023

Extensive research has been conducted to address the growing global demand for copper by exploring effective methods of extraction and recovery across various industries. The emulsion liquid membrane (ELM) has emerged as a viable option for efficiently extracting and recovering metals from waste solutions. Due to its advantageous features, the extraction and recovery of copper from a simulated copper solution was investigated. In the ELM, various parameters can affect the stability and efficiency of copper extraction which include agitation speed, treat ratio (TR), stripping agent, and carrier concentration. However, certain parameters such as homogenizer speed, emulsification time, surfactant concentration, extraction time, and pH of the simulated feed solution were kept constant in this study. The most favourable parameters for achieving maximum copper extraction and recovery were determined such as TR of 1:3, agitation speed (250 rpm), LIX 84 (0.2 M) in kerosene as the carrier, and H2SO4 (0.5 M) as the stripping agent. Using these conditions, approximately 74% of the copper was extracted while 37% was recovered with an acceptable ELM stability indicated by a 20% membrane swelling. This research demonstrates the significant potential of the ELM process for extracting copper from wastewater generated by various industries.
KATP channel activity and slow oscillations in pancreatic beta cells are regulated by mitochondrial ATP production
Authors: Corradi Jeremías , Thompson Benjamin , Fletcher Patrick A. , Bertram Richard , Sherman Arthur S. , Satin Leslie S.
Published: November 2023

Pancreatic beta cells secrete insulin in response to plasma glucose. The ATP‐sensitive potassium channel (KATP) links glucose metabolism to islet electrical activity in these cells by responding to increased cytosolic [ATP]/[ADP]. It was recently proposed that pyruvate kinase (PK) in close proximity to beta cell KATP locally produces the ATP that inhibits KATP activity. This proposal was largely based on the observation that applying phosphoenolpyruvate (PEP) and ADP to the cytoplasmic side of excised inside‐out patches inhibited KATP. To test the relative contributions of local vs. mitochondrial ATP production, we recorded KATP activity using mouse beta cells and INS‐1 832/13 cells. In contrast to prior reports, we could not replicate inhibition of KATP activity by PEP + ADP. However, when the pH of the PEP solutions was not corrected for the addition of PEP, strong channel inhibition was observed as a result of the well‐known action of protons to inhibit KATP. In cell‐attached recordings, perifusing either a PK activator or an inhibitor had little or no effect on KATP channel closure by glucose, further suggesting that PK is not an important regulator of KATP. In contrast, addition of mitochondrial inhibitors robustly increased KATP activity. Finally, by measuring the [ATP]/[ADP] responses to imposed calcium oscillations in mouse beta cells, we found that oxidative phosphorylation could raise [ATP]/[ADP] even when ADP was at its nadir during the burst silent phase, in agreement with our mathematical model. These results indicate that ATP produced by mitochondrial oxidative phosphorylation is the primary controller of KATP in pancreatic beta cells.

image

Key points

Phosphoenolpyruvate (PEP) plus adenosine diphosphate does not inhibit KATP activity in excised patches. PEP solutions only inhibit KATP activity if the pH is unbalanced.

Modulating pyruvate kinase has minimal effects on KATP activity.

Mitochondrial inhibition, in contrast, robustly potentiates KATP activity in cell‐attached patches.

Although the ADP level falls during the silent phase of calcium oscillations, mitochondria can still produce enough ATP via oxidative phosphorylation to close KATP.

Mitochondrial oxidative phosphorylation is therefore the main source of the ATP that inhibits the KATP activity of pancreatic beta cells.
Enhanced motor learning and motor savings after acute intermittent hypoxia are associated with a reduction in metabolic cost
Authors: Bogard Alysha T. , Hemmerle Makenna R. , Smith Andrew C. , Tan Andrew Q.
Published: November 2023

Breathing mild bouts of low oxygen air (i.e. acute intermittent hypoxia, AIH) has been shown to improve locomotor function in humans after a spinal cord injury. How AIH‐induced gains in motor performance are achieved remains unclear. We examined the hypothesis that AIH augments motor learning and motor retention during a locomotor adaptation task. We further hypothesized that gains in motor learning and retention will be associated with reductions in net metabolic power, consistent with the acquisition of energetically favourable mechanics. Thirty healthy individuals were randomly allocated into either a control group or an AIH group. We utilized a split‐belt treadmill to characterize adaptations to an unexpected belt speed perturbation of equal magnitude during an initial exposure and a second exposure. Adaptation was characterized by changes in spatiotemporal step asymmetry, anterior–posterior force asymmetry, and net metabolic power. While both groups adapted by reducing spatial asymmetry, only the AIH group achieved significant reductions in double support time asymmetry and propulsive force asymmetry during both the initial and the second exposures to the belt speed perturbation. Net metabolic power was also significantly lower in the AIH group, with significant reductions from the initial perturbation exposure to the second. These results provide the first evidence that AIH mediates improvements in both motor learning and retention. Further, our results suggest that reductions in net metabolic power continue to be optimized upon subsequent learning and are driven by more energetically favourable temporal coordination strategies. Our observation that AIH facilitates motor learning and retention can be leveraged to design rehabilitation interventions that promote functional recovery.

image

Key points

Brief exposures to low oxygen air, known as acute intermittent hypoxia (AIH), improves locomotor function in humans after a spinal cord injury, but it remains unclear how gains in motor performance are achieved.

In this study, we tested the hypothesis that AIH induces enhancements in motor learning and retention by quantifying changes in interlimb coordination, anterior–posterior force symmetry and metabolic cost during a locomotor adaptation task.

We show the first evidence that AIH improves both motor learning and savings of newly learned temporal interlimb coordination strategies and force asymmetry compared to untreated individuals.

We further demonstrate that AIH elicits greater reductions in metabolic cost during motor learning that continues to be optimized upon subsequent learning.

Our findings suggest that AIH‐induced gains in locomotor performance are facilitated by enhancements in motor learning and retention of more energetically favourable coordination strategies.
Explainability of Laser Powder Bed Fusion Melt Pool Classification Using Deep Learning
Authors: Sato Matthew M. , Wong Vivian Wen Hui , Law Kincho H. , Yeung Ho , Witherell Paul
Published: November 2023

Laser powder bed fusion (LPBF) has shown enormous potential for metal additive manufacturing in recent years. However, the relationship between the LPBF process parameters and part quality is not yet fully understood. Some LPBF machines now use cameras to monitor melt pools during manufacturing. Machine learning techniques have been proposed to analyze the melt pool data and to evaluate the quality of the manufacturing process. However, these machine learning techniques often appear as a black box and the underlying decisions made by the machine learning models are unknown. This paper proposes a neural network to classify the melt pool shapes using melt pool images and process parameters as model inputs. With both process parameters and the melt pool image being included, an explainable artificial intelligence (XAI) approach is developed to interpret the neural network and understand the relationships between the melt pool shape and the process parameters. Specifically, layer-wise relevance propagation (LRP) is used to reveal the relevance of process parameters in the neural network’s decision-making. Using LRP, relationships between the process parameters and melt pool shapes are revealed without explicit knowledge of the underlying physics. These relationships can potentially be used to adjust the process parameters and improve the quality of LPBF manufactured parts. This paper demonstrates how neural networks and XAI can effectively identify relationships between process parameters and LPBF melt pools.
Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications
Authors: Picard Cyril , Schiffmann Jürg , Ahmed Faez
Published: November 2023

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significant challenge for researchers aiming to apply these breakthroughs in engineering design. Synthetic datasets emerge as a viable alternative. However, practitioners are often uncertain about generating high-quality datasets that accurately represent real-world data and are suitable for the intended downstream applications. This study aims to fill this knowledge gap by proposing comprehensive guidelines for generating, annotating, and validating synthetic datasets. The trade-offs and methods associated with each of these aspects are elaborated upon. Further, the practical implications of these guidelines are illustrated through the creation of a turbo-compressors dataset. The study underscores the importance of thoughtful sampling methods to ensure the appropriate size, diversity, utility, and realism of a dataset. It also highlights that design diversity does not equate to performance diversity or realism. By employing test sets that represent uniform, real, or task-specific samples, the influence of sample size and sampling strategy is scrutinized. Overall, this paper offers valuable insights for researchers intending to create and publish synthetic datasets for engineering design, thereby paving the way for more effective applications of AI advancements in the field. The code and data for the dataset and methods are made publicly accessible at https://github.com/cyrilpic/radcomp.
Non-Contact Measurement of Spiral Bevel Gears Using the Laser Profiler on the Five-Axis Machine
Authors: Shih Yi-Pei , Sheen Bor-Tyng , Wu Wun-Kai , Wei Bo-Lin
Published: November 2023

Nowadays, the measuring machines for gears, such as the P series of Klingelnberg and the GMS series of Gleason, are all four-axis structures. They have a three-dimensional contact scanning probe system and high measurement accuracy. This measurement has two main disadvantages: (1) it is time-consuming, and (2) difficult to measure small-size gears with less than a 0.5 mm module. Due to the above drawbacks, non-contact measurement has become more popular recently.

This research aims to develop a non-contact measurement system of spiral bevel gears using a laser profiler. We establish the coordinate systems of the measuring machine. This machine has five axes, four for measuring movement and one for the orientation of the laser profiler. The five coordinates of pitch and tooth flank measurements are derived according to theoretical gear flank points. The NC codes are programmed for measuring the pitch and tooth flank of bevel gears according to those coordinates. After that, we propose a method based on DIN 3965-2 to evaluate the pitch and tooth flank errors. Here, a double-rotary-table type five-axis machine is adopted as an experiment machine. The results are compared to the report of the Klingelnberg P40 gear measuring center. Their pitch and the maximum tooth flank deviations are within 0.004 and 0.05 mm, respectively. Those results verify the correctness of the proposed method.
Evaluating Heart-Rate Variability Metrics As a Measure of Stress During Unsedated Medical Procedures
Authors: Cameron Chris J. , Pretty Christopher G. , Bagshaw Phil , Aramowicz Jaana , Hayes Michael P.
Published: November 2023

Heart rate variability (HRV) has been proposed as a measure of psychophysiological stress, however validations often focus on complex stressors that may cause non-stress arousal. We investigate the efficacy of a range of HRV metrics as an objective measure of stress during an unsedated flexible sigmoidoscopy procedure on 47 patients. HRV metrics were calculated at several epochs across the procedure. Acceleration and deceleration capacity, the standard deviation of normal-normal intervals, high-frequency power, and the α1 parameter of detrended fluctuation analysis all showed a significant difference between stressed and unstressed states, to p < 0.0167. Low-frequency power and the low:high frequency ratio both exhibited trends in an unexpected direction, casting doubt on their suitability. The root-mean-square of successive differences and sample entropy failed to differentiate between stressed and unstressed states.

Measured effect sizes and standard deviations, combined with population norm values, were used to calculate sample sizes for future studies. Acceleration and deceleration capacities, the standard deviation of normal-normal intervals, and α1 provided the highest power with low sample sizes, allowing well-powered tests a n < 100 for a reduction in stress of 75% or greater. Other metrics which successfully identified stress had large variances that ruled out well-powered trials in small samples.
GradeS: An AI-Driven Graphic Design Support System for Design Style Analysis
Authors: Song Jinyu , You Weitao , Shi Shuhui , Tu Ziwei , Ji Juntao , Han Kaixin , Sun Lingyun
Published: November 2023

The style of graphic design is an important design factor that influences the memorability of designs. Graphic designers routinely analyze the latest designs, capture the style trends, and create designs that match the style trends to appeal to a larger audience. Nonetheless, the lack of quantitative style analysis techniques can lead to an inefficient analysis process and introduce subjectivity and bias. To expedite designers’ understanding of design style trends and make the analysis more objective, we propose GradeS, an AI-driven graphic design support system that facilitates multifaceted quantitative analysis of graphic design style. The system was designed and developed in collaboration with designers and comprises four primary interfaces: GradeS:S, GradeS:Q, GradeS:C, and GradeS:T, each serving specific needs identified through interviews with designers. We leveraged the Vision Transformer to model the one-to-many relationship between designs and styles and implemented all interfaces based on the quantitative style representation learned by the model. To train the model, we built a graphic design dataset with carefully designed coarse-grained style labels. We have released the dataset to the community to promote research in data-driven design. To demonstrate the effectiveness of our study, we evaluated both the model and the system. Our model exhibits superior performance in style classification compared to CLIP. Through a user study involving six designers, our system’s effectiveness in supporting designers in analyzing style quantitatively, capturing style trends comprehensively and quickly, and further stimulating creative thinking was demonstrated.
A Compliant Hinge Joint Driven by the PneuNets Bending Actuator for Enhancing the Performance of Soft Robots
Authors: Jin Yi , Su Hai-Jun
Published: November 2023

While soft robots enjoy the benefits of high adaptability and safety, their inherent flexibility makes them suffer from lower load-carrying capacity and low motion precision, which limits their applications to a broader range of fields. In this paper, we propose an active hinge joint with a hard backbone combined with soft pneumatic actuators to overcome this challenge. We detail the design, theoretical modeling, and experimental testing of a novel compliant hinge joint driven by two pneumatic networks (PneuNets) bending actuators. The joint is constructed by attaching the two actuators to a cross-spring pivot’s two flexible leaf springs. Pressurizing one of the actuators can drive the joint to rotate clockwise or counterclockwise about the central axis. A Pseudo-rigid-body model is developed to analyze the kinematics and statics of the joint. FEA simulation and experimental experiments have been developed to validate the model. The results show that the joint can achieve ± 43° under 0.276 MPa, and the pressure-displacement curve is close to linear. Experiments are also conducted to measure the joint’s in-axis and the other three off-axis stiffness. After calculating the stiffness ratio, the results show that the three off-axis stiffness (Kθx, KY, KZ) are 16.74, 471.75, and 627.63 times the in-axis stiffness (Kθz), respectively. It means our hinge joint can carry a high payload off-axis while maintaining the in-axis flexibility.
Interpretable Neural Network Analyses for Understanding Complex Physical Interactions in Engineering Design
Authors: Dolar Tuba , Lee Doksoo , Chen Wei
Published: November 2023

In engineering design, global sensitivity analysis (GSA) is used for analyzing the effects of the system inputs on the model response. Common GSA methods use analytical or surrogate models to study the relationships between model inputs and outputs. However, the accuracy of such system models depends on the complete conformance to all model assumptions. Even so, they are not flexible and fail to capture nonlinear behaviors in complex systems. Besides these GSA approaches, interpretable machine learning would also identify the relationships between system variables, eliminating the disadvantages of common GSA implementations. Apart from studying the independent variables individually, the evaluation of groups of them is likewise valuable. One example motivation in engineering design for performing GSA with groups of input variables would be managing the design space complexity in programmable material systems (PMS) development. In this article, we employ a flexible, interpretable artificial neural network model to uncover individual as well as grouped global sensitivity indices for understanding complex physical interactions in engineering design. The employed model allows the investigation of the feature importance of the main effects and pairwise interaction effects in GSA according to functional analysis of variance (ANOVA) decomposition. To draw a higher-level understanding, we further use a subset decomposition method to analyze the significance of the groups of input variables. Using PMS as an example, we demonstrate the use of our approach for understanding the impact of material, architecture, and stimulus variables as well as their interactions for a programmable photonic metasurface system. This information lays the foundation for deriving design guidelines for PMS development.
Multiphysics Missing Data Synthesis (MiDaS): A Machine-Learning Approach for Mitigating Data Gaps and Artifacts
Authors: Steuben John C. , Geltmacher Andrew B. , Rodriguez Steven N. , Graber Benjamin D. , Iliopoulos Athanasios P. , Michopoulos John G.
Published: November 2023

The presence of gaps and spurious non-physical artifacts in datasets is a nearly ubiquitous problem in many scientific and engineering domains. In the context of multiphysics numerical models, data gaps may arise from lack of coordination between modeling elements and limitations of the discretization and solver schemes employed. In the case of data derived from physical experiments, the limitations of sensing and data acquisition technologies, as well as myriad sources of experimental noise, may result in the generation of data gaps and artifacts. In the present work we develop and demonstrate a machine learning (ML) meta-framework for repairing such gaps in multiphysics datasets. A unique “cross-training” methodology is used to ensure that the ML models capture the underlying multiphysics of the input datasets, without requiring training on datasets free of gaps/artifacts. The general utility of this approach is demonstrated by the repair of gaps in a multiphysics dataset taken from hypervelocity impact simulations. Subsequently, we examine the problem of removing scan artifacts from X-ray computed micro-tomographic (XCMT) datasets. A unique experimental methodology for acquiring XCMT data, wherein articles are scanned multiple times under different conditions, enables the ready identification of artifacts, their removal from the datasets, and the filling of the resulting gaps using the ML framework. This work concludes with observations regarding the unique features of the developed methodology, and a discussion of potential future developments and applications for this technology.
When Is it Actually Worth Learning Inverse Design?
Authors: Habibi Milad , Wang Jun , Fuge Mark
Published: November 2023

Design optimization, and particularly adjoint-based multi-physics shape and topology optimization, is time-consuming and often requires expensive iterations to converge to desired designs. In response, researchers have developed Machine Learning (ML) approaches — often referred to as Inverse Design methods — to either replace or accelerate tools like Topology optimization (TO). However, these methods have their own hidden, non-trivial costs including that of data generation, training, and refinement of ML-produced designs. This begs the question: when is it actually worth learning Inverse Design, compared to just optimizing designs without ML assistance?

This paper quantitatively addresses this question by comparing the costs and benefits of three different Inverse Design ML model families on a Topology Optimization (TO) task, compared to just running the optimizer by itself. We explore the relationship between the size of training data and the predictive power of each ML model, as well as the computational and training costs of the models and the extent to which they accelerate or hinder TO convergence. The results demonstrate that simpler models, such as K-Nearest Neighbors and Random Forests, are more effective for TO warmstarting with limited training data, while more complex models, such as Deconvolutional Neural Networks, are preferable with more data. We also emphasize the need to balance the benefits of using larger training sets with the costs of data generation when selecting the appropriate ID model. Finally, the paper addresses some challenges that arise when using ML predictions to warmstart optimization, and provides some suggestions for budget and resource management.
The Presence of Chaos in a Viscoelastic Harmonically Forced Von Mises Truss
Authors: Ghoshal Pritam , Gibert James , Bajaj Anil K.
Published: November 2023

This paper examines the effect of viscoelasticity on the dynamic behavior of a bistable dome-shaped structure represented as a lumped parameter viscoelastic von Mises truss. The viscoelastic system is governed by a third order jerk equation. The presence of viscoelasticity also introduces additional time scales and degrees of freedom into the problem when compared to their viscous counterparts, thus making the study of these systems in the presence of harmonic loading even more interesting. It is highly likely that the system would exhibit non-regular behavior for some combination of forcing frequency and forcing amplitude. With this motivation, we start by studying the dynamics of a harmonically forced von Mises truss in the presence of viscous damping only. This leads to a Duffing type equation with an additional quadratic non-linearity. We demonstrate some of the rich dynamic behavior that this system exhibits in some parameter ranges. This provides useful insight into the possible behavior of the viscoelastic system. The viscous damper is then replaced by a viscoelastic unit. We show that the system can exhibit both regular as well as chaotic behavior. The threshold limit for the chaotic motion has been determined using Melnikov’s criteria and verified through numerical simulations using the largest Lyapunov exponent.
Data-Driven Control Co-Design for Indirect Liquid Cooling Plate With Microchannels for Battery Thermal Management
Authors: Liu Zheng , Xu Yanwen , Wu Hao , Wang Pingfeng , Li Yumeng
Published: November 2023

The demand for high-performance electric vehicles keeps increasing with the booming electric vehicles market. Thus, battery cooling is significant in enabling the battery to work under harsh discharge process. Thanks to its high efficiency and low cost, indirect liquid cooling is a widely used cooling method for batteries. Researchers are trying to optimize the plant or control design separately for a better cooling effect. However, they can only produce suboptimal results with low efficiency. Motivated by the imperfections of existing battery cooling systems, we aim to lower the cost of indirect liquid cooling for batteries considering the plant design and control design using data-driven co-design optimization. First, a finite element model of the battery was built to predict the temperature and validate our findings against experimental data. Then, a Gaussian process-based surrogate model combined with Monte Carlo simulation extended the prediction to many scenarios under harsh discharge process. Finally, the surrogate model obtained the optimal plant and control designs. The finite element model validated the optimal design, which lowered the cost by 10%.