bluuebunny/crossref_metadata_2025 huggingface dataset:
Corrosion Investigation by Scanning Electrochemical Microscopy of AISI 446 and Ti-Coated AISI 446 Ferritic Stainless Steel as Potential Material for Bipolar Plate in PEMWE
Authors: Kellenberger Andrea , Vaszilcsin Nicolae , Dan Mircea Laurentiu , Mitelea Ion , Geana Alexandru Adrian , Lædre Sigrid , Craciunescu Corneliu M.
Published: January 2024

The components of proton exchange membrane water electrolysers frequently experience corrosion issues, especially at high anodic polarization, that restrict the use of more affordable alternatives to titanium. Here, we investigate localized corrosion processes of bare and Ti-coated AISI 446 ferritic stainless steel under anodic polarization by scanning electrochemical microscopy (SECM) in sodium sulphate and potassium chloride solutions. SECM approach curves and area scans measured at open-circuit potential (OCP) of the samples in the feedback mode using a redox mediator evidence a negative feedback effect caused by the surface passive film. For the anodic polarization of the sample, the substrate generation-tip collection mode enables to observe local generation of iron (II) ions, as well as formation of molecular oxygen. For the uncoated AISI 446 sample, localized corrosion is detected in sodium sulphate solution simultaneously with oxygen formation at anodic potentials of 1.0 V vs. Ag/AgCl, whereas significant pitting corrosion is observed even at 0.2 V vs. Ag/AgCl in potassium chloride solution. The Ti-coated AISI 446 sample reveals enhanced corrosion resistance in both test solutions, without any evidence of iron (II) ions generation at anodic potentials of 1.2 V vs. Ag/AgCl, where only oxygen formation is observed.
Association between accelerometry measured patterns of sedentary behaviors and functional status in older adults
Authors: Son Jung Yoen , Zhou Weijiao , Webster-Dekker Katelyn E. , Marriott Deanna J. , Larson Janet L.
Published: January 2024

Background

Older adults are highly sedentary, and too much sedentary behavior (SB) is associated with negative health effects, but little is known about SB patterns and their associations with functional status.

Aims

To examine the association between objectively measured sedentary behavior time (SBT) and sedentary behavior fragmentation (SBF) and functional status in older adults using the National Health Aging Trends Study (NHATS) dataset, a nationally representative sample from 2021.

Methods

Data from NHATS were analyzed using weighted linear regressions to examine the association between objective measures of SBT (mean hours spent in SB/day during waking hours) and SBF, and six functional variables (difficulties with activities of daily living [ADL], short physical performance battery, hand grip strength, immediate word recall, delayed word recall, and mental health), accounting for sociodemographic, body mass index, and the number of chronic conditions.

Results

A total of 738 individuals from the NHATS were included. Higher SBT was associated with greater difficulties with ADL, poorer short physical performance battery and hand grip strength, lower scores in both immediate and delayed word recall, and poorer mental health. Higher SBF was associated with fewer difficulties with ADL, better short physical performance battery and hand grip strength, a higher score in immediate word recall, and better mental health.

Discussionand conclusions

Greater fragmentation of SB was associated with better function, and increasing SBF may be a useful strategy for mitigating the effects of SB in older adults, but prospective research is needed to support this approach.
Development and validation of prediction model for older adults with cognitive frailty
Authors: Huang Jundan , Zeng Xianmei , Ning Hongting , Peng Ruotong , Guo Yongzhen , Hu Mingyue , Feng Hui
Published: January 2024

Objective

This study sought to develop and validate a 6-year risk prediction model in older adults with cognitive frailty (CF).

Methods

In the secondary analysis of Chinese Longitudinal Healthy Longevity Survey (CLHLS), participants from the 2011–2018 cohort were included to develop the prediction model. The CF was assessed by the Chinese version of Mini-Mental State Exam (CMMSE) and the modified Fried criteria. The stepwise regression was used to select predictors, and the logistic regression analysis was conducted to construct the model. The model was externally validated using the temporal validation method via the 2005–2011 cohort. The discrimination was measured by the area under the curve (AUC), and the calibration was measured by the calibration plot. A nomogram was conducted to vividly present the prediction model.

Results

The development dataset included 2420 participants aged 60 years or above, and 243 participants suffered from CF during a median follow-up period of 6.91 years (interquartile range 5.47–7.10 years). Six predictors, namely, age, sex, residence, body mass index (BMI), exercise, and physical disability, were finally used to develop the model. The model performed well with the AUC of 0.830 and 0.840 in the development and external validation datasets, respectively.

Conclusion

The study could provide a practical tool to identify older adults with a high risk of CF early. Furthermore, targeting modifiable factors could prevent about half of the new-onset CF during a 6-year follow-up.
Normalized stability time analysis within the boundaries between adults with and without fear of falling
Authors: Lee Dongchul , Sung Paul S.
Published: January 2024

Background

The unilateral stance test, measured by the center of pressure (COP), has been widely used to identify balance deficits. However, there is a critical gap in understanding the specific COP thresholds on postural stability in adults with a fear of falling (FOF).

Aims

To investigate the normalized stability time, which was defined as the ratio of time spent within stability boundaries to the total test duration, under different visual conditions and specific thresholds between adults with and without FOF.

Methods

Twenty-one older adults with FOF and 22 control subjects completed the unilateral limb standing test in eyes-open and eyes-closed conditions. Normalized stability times were computed based on five pre-determined COP sway range thresholds: 10 mm, 15 mm, 20 mm, 25 mm, and 30 mm.

Results

Receiver operating characteristic analysis determined the diagnostic accuracy of FOF. There were significant differences in the effects of both visual conditions (F = 46.88, p = 0.001) and threshold settings (F = 119.38, p = 0.001) on stability time between groups. The FOF group significantly reduced normalized stability time at the 10 mm COP threshold under eyes-closed conditions (t = – 1.95, p = 0.03).

Discussion

The findings highlight the heightened sensitivity of the 10 mm COP threshold in identifying group variances in postural stability when eyes are closed. Moreover, the FOF group displayed a marked reduction in stability duration based on visual scenarios and normalized thresholds.

Conclusion

The study highlights the need to account for both COP boundaries and visual conditions in adults with FOF. When assessing postural control during unilateral stances, clinicians must also give attention to non-visual cues.
One-leg standing time is a simple measure for loss of skeletal muscle mass and fat deposition in muscle: the J-SHIPP study
Authors: Tabara Yasuharu , Okada Yoko , Ochi Masayuki , Ohyagi Yasumasa , Igase Michiya
Published: January 2024

Backgrounds

One-leg standing time (OLST) has been frequently used physical performance measure; however, what muscular characteristics OLST represents remains uncertain.

Aim

This cross-sectional study aimed to investigate the association between OLST and muscle characteristics to clarify the possibility of using OLST as a physical performance measure.

Methods

Study participants comprised 1144 older adults aged 65 years or older. Computed tomography images provided mid-thigh skeletal muscle cross-sectional area and mean attenuation value. OLST was measured for a maximum of 60 s. Static postural instability was assessed using a posturography.

Results

A frequency of OLST < 20 s was increased by quartiles of muscle cross-sectional area (Q1: 33.6, Q2: 12.8, Q3: 13.6, Q4: 11.9%, P < 0.001) and mean attenuation value (Q1: 32.3, Q2: 21.7, Q3: 14.3, Q4: 7.7%, P < 0.001). Results of the multinomial regression analysis indicated that muscle cross-sectional area and mean attenuation value were independently associated with an OLST of less than 20 s. The crude odds ratio of OLST less than 20 s for the lowest quartiles of both cross-sectional area and mean attenuation value was 4.19 (95% CI: 3.01 − 5.84). The cross-sectional area of muscles with greater fat deposition was inversely associated with OLST, while that with smaller fat deposition showed a positive association with OLST, indicating why mean attenuation value and cross-sectional area were independently associated with OLST. No clear relationship was observed with static postural instability.

Conclusion

OLST was a simply measurable quantifiable physical measure representing the loss of muscle mass and quality in older adults.
Association between low values of mean arterial pressure and impaired cognitive performance in older patients with mild cognitive impairment: cross-sectional preliminary findings from the STRENGTH Project
Authors: Santillo Elpidio , Balietti Marta , Fabbietti Paolo , Antolini Maria Sole , Paoloni Cristina , Piacenza Francesco , Giuli Cinzia
Published: January 2024

Background

Uncontrolled blood pressure (BP) is a risk factor for Mild Cognitive Impairment (MCI) and dementia.

Aims

This study examined the relationship between BP and clinical/cognitive/neuropsychological aspects in MCI individuals.

Methods

MCI patients underwent clinical, functional, cognitive and metacognitive, as well as psychological assessments. Social network, lifestyle characteristics, and medication prescriptions were also evaluated. Each patient underwent BP measurements.

Results

Lower values of systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP) were associated with poorer cognitive performance. Notably, MAP showed greater capability in detecting impairments in attention and visuospatial abilities compared to SBP and DBP.

Discussion

These findings support the notion that in older individuals with MCI excessively low BP values, particularly MAP, might represent a risk and suggest that cerebral hypoperfusion may play a key role.

Conclusions

Routine assessment of MAP could aid clinicians in adjusting antihypertensive treatment and closely monitoring cognitive function in MCI patients.
The relationship between circulating metabolites and prostate hyperplasia: a Mendelian randomization study
Authors: Zhang Ze-chao , Huang Shu-ping , Lin Ze-sen , Chen Yu , Jiang Peng , Yang Yu-wei , Shang Chang-jie , Zhu Min , Gao Hong-jun
Published: January 2024

Background

Circulating metabolites (CM) play a pivotal role in our overall health, yet the current evidence concerning the involvement of diverse CM in benign prostatic hyperplasia (BPH) remains limited. Mendelian randomization (MR) offers a promising avenue to explore the potential impact of CM on BPH.

Methods

In a forward MR analysis, a cohort of 249 circulating metabolites was employed as exposures to investigate their potential associations with BPH risk. Conversely, in a reverse MR analysis, BPH was employed as an exposure to assess its effects on CM.

Results

The forward MR analysis discerned a linkage between six metabolites and BPH, with careful consideration to excluding heterogeneity and pleiotropy. Subsequently, the reverse MR analysis unveiled that nine metabolic compounds, mainly comprising phospholipids and triglycerides, potentially exhibit elevated levels in BPH patients.

Conclusion

Bidirectional MR analysis furnishes genetic insight into the interplay between CM and BPH. The prominence of lipids and triglycerides emerges as significant factors intricately linked to BPH risk.
Prevalence of sarcopenia in Africa: a systematic review and meta-analysis of observational studies
Authors: Veronese Nicola , Smith Lee , Koyanagi Ai , Hoffman Jaco , Snoussi Mouna , Prokopidis Konstantinos , Dominguez Ligia J. , Barbagallo Mario
Published: January 2024

Background

Existing literature suggests that sarcopenia is a highly prevalent condition in older people. However, most studies to date reporting data on its prevalence have been mainly carried out in Western countries, while data on sarcopenia in Africa is scarce. With this systematic review and meta‐analysis, we aimed to determine the prevalence of sarcopenia in African countries and to explore potential factors that could explain higher or lower prevalence of this condition in Africa.

Methods

Major databases for studies reporting data on sarcopenia in African countries were searched from inception to June 2023. We conducted a meta-analysis of the prevalence [and 95% confidence intervals (95% CIs)] of sarcopenia in Africa, applying a random effect model. Several sensitivity and meta-regression analyses were run.

Results

Among 147 articles initially screened, six articles (with seven cohorts) including a total of 10,656 participants were included. Mean age of participants was 66.9 years, and the majority were female (58.1%). The weighted prevalence of sarcopenia in the selected countries of Africa was 25.72% (95%CI: 18.90–32.55). This outcome was characterized by a high heterogeneity (I2 = 99%) and by publication bias. Among the factors investigated, sarcopenia was lower when assessed using only one anthropometric measure, or in South Africa.

Conclusion

Sarcopenia is a prevalent condition in Africa and thus research regarding this topic is a public health priority. Future studies that cover African countries for which data are not available and using standardized criteria are needed.
Where To Go at the Next Timestamp
Authors: Duan Jiaqi , Meng Xiangfu , Liu Guihong
Published: January 2024

The next Point of Interest (POI) recommendation is the core technology of smart city. Current state-of-the-art models attempt to improve the accuracy of the next POI recommendation by incorporating temporal and spatial intervals or by partitioning the POI coordinates into grids. However, they all overlook a detail that in real life, people always want to know where to go at an exact time point or after a specific time interval instead of aimlessly asking where to go next. Moreover, due to individual preferences, different users may visit different places at the same timestamp. Therefore, utilizing timestamp queries can enhance the personalized recommendation capability of the model and mitigate overfitting risks. These implies that using timestamp can achieve more precise recommendations. To the best of our knowledge, we are the first to use the next timestamp for next POI recommendation. In particular, we propose a Time-Stamp Cross Attention Network (TSCAN). TSCAN is a two-layer cross-attention network. The first layer, Time Stamp Cross Attention Block (TSCAB), uses cross-attention between the next timestamp and historical timestamps, and multiplies the attention scores on corresponding POI to predict the next POI that is most related to the history. The other layer, Cross Time Interval Aware Block (CTIAB), applies the time intervals between the next timestamp and historical timestamps to the POI obtained by TSCAB and historical POIs, allowing temporally adjacent POIs to have a greater similarity. Our model not only has a significant improvement in accuracy but also achieves the goal of personalized recommendation, effectively alleviating overfitting. We evaluate the proposed model with three real-world LBSN datasets, and show that TSCAN outperforms the state-of-the-art next POI recommendation models by 5~9%. TSCAN can not only recommend the next POI, but also recommend the possible POI to visit at any specific timestamp in the future.
Bayesian prediction and estimation based on a shrinkage prior for a Poisson regression model
Authors: Komaki Fumiyasu
Published: January 2024

We introduce a Poisson regression model with a natural structure, as viewed from the perspective of information geometry. A shrinkage prior distribution can be utilized similarly to the multi-dimensional Poisson distribution. In the Poisson regression model, we demonstrate that the Bayes extended estimator and Bayesian predictive density based on the shrinkage prior dominate those based on the Jeffreys prior under the Kullback–Leibler loss. By considering a multi-dimensional Poisson process, we show that the loss of the Bayesian predictive density is expressed as the integral of the loss of the Bayes extended estimators. Additionally, we discuss on the numerical evaluation of the Bayes extended estimates
Characterizing Radiation‐Belt Energetic Electron Precipitation Spectra: A Comparison of Quasi‐Linear Diffusion Theory With In Situ Measurements
Authors: Reidy J. A. , Horne R. B. , Glauert S. A. , Clilverd M. A. , Meredith N. P. , Rodger C. J. , Ross J. P. , Wong J.
Published: January 2024

High energy electron precipitation from the Earth's radiation belts is important for loss from the radiation belts and atmospheric chemistry. We follow up investigations presented in Reidy et al. (2021, https://doi.org/10.1029/2020ja028410) where precipitating flux is calculated inside the field of view of the POES T0 detector using quasi‐linear theory and pitch angle diffusion coefficients (Dαα) from the British Antarctic Survey (BAS). These results showed good agreements at >30 keV for L* >5 on the dawnside but the flux were too low at higher energies. We have investigated the effect of changing parameters in the calculation of the precipitating flux to improve the results for the higher energies using comparisons of in situ flux and cold plasma measurements from GOES‐15 and RBSP. We find that the strength of the diffusion coefficients rather than the shape of the source spectrum has the biggest effect on the calculated precipitation. In particular we find decreasing the cold plasma density used in the calculation of Dαα increases the diffusion and hence the precipitation at the loss cone for the higher energies, improving our results. The method of calculating Dαα is also examined, comparing co‐located rather than averaged RBSP measurements. We find that the method itself has minimal effect but using RBSP derived Dαα improved our results over using Dαα calculated using the entire BAS wave data base; this is potentially due to better measurements of the cold plasma density from RBSP than the other spacecraft included in the BAS wave data base (e.g., THEMIS).
Seasonal Variations of Sq Current System in Different Longitudinal Sectors and Solar Activities
Authors: Liu Xiaocan , Han Peng , Hattori Katsumi , Chen Huaran , Chen Junjie , Jiao Liguo , Tu Jiyao , Lei Yu , Zhao Junhao
Published: January 2024

Years of geomagnetic observatory data during the geomagnetic quiet days (Kp ≤ 3) at the low and middle dip latitudes from INTERMAGNET and SuperMAG were utilized. Seasonal models of Sq currents for two longitudinal chains at each year and under two solar activity levels (F10.7 index are ∼75 and 125 sfu) were constructed by spherical harmonic analysis. It is found that there are significant seasonal variations of Sq currents in the Asian‐Oceanian (A‐O) and North‐South American (N‐SA) longitude sectors under different solar activities. First, the focus intensity J increases faster in local winter than in summer for both two hemispheres as solar activity strengthens. J of ionospheric currents in the northern hemisphere (NH) during local winter is higher than that in the southern hemisphere during its winter. This asymmetric activity in the N‐SA chain increases with the solar activity becomes stronger. Second, with solar activity increases, the ionospheric current focus of N‐SA chain in the NH shifts toward the lower latitudes during two solstices, while internal current focus of both two chains move toward the lower latitudes during the December solstice. Seasonal variations of Sq currents in the two chains exhibit longitudinal effects. With increasing solar activity, the two hemispheric focuses of the ionospheric currents in the A‐O chain both move closer to the midday longitude sector, while in the N‐SA chain, only the focus in the NH shifts toward noon. The results reveal details of the seasonal variations of Sq currents.
Influence of the Jovian Current Sheet Models on the Mapping of the UV Auroral Footprints of Io, Europa, and Ganymede
Authors: Rabia J. , Nénon Q. , André N. , Hue V. , Santos‐Costa D. , Kamran A. , Blanc M.
Published: January 2024

The in situ characterization of moon‐magnetosphere interactions at Jupiter and the mapping of moon auroral footpaths require accurate global models of the magnetospheric magnetic field. In this study, we compare the ability of two widely‐used current sheet models, Khurana‐2005 (KK2005) and Connerney‐2020 (CON2020) combined with the most recent internal magnetic field model of Jupiter (JRM33) to match representative Galileo and Juno measurements acquired at low, medium, and high latitudes. With the adjustments of the KK2005 model to JRM33, we show that in the outer and middle magnetosphere (R > 15RJ), JRM33 + KK2005 is found to be the best model to reproduce the magnetic field observations of Galileo and Juno as it accounts for local time effects. JRM33 + CON2020 gives the most accurate representation of the inner magnetosphere. This finding is drawn from comparisons with Juno in situ magnetic field measurements and confirmed by contrasting the timing of the crossings of the Io, Europa, and Ganymede flux tubes identified in the Juno particles data with the two model estimates. JRM33 + CON2020 also maps more accurately the UV auroral footpath of Io, Europa, and Ganymede observed by Juno than JRM33 + KK2005. The JRM33 + KK2005 model predicts a local time asymmetry in position of the moons' footprints, which is however not detected in Juno's UV measurements. This could indicate that local time effects on the magnetic field are marginal at the orbital locations of Io, Europa, and Ganymede. Finally, the accuracy of the models and their predictions as a function of hemisphere, local time, and longitude is explored.
Automatic Encoding of Unlabeled Two Dimensional Data Enabling Similarity Searches: Electron Diffusion Regions and Auroral Arcs
Authors: Smith A. W. , Rae I. J. , Stawarz J. E. , Sun W. J. , Bentley S. , Koul A.
Published: January 2024

Critically important phenomena in Earth’s magnetosphere often occur briefly, or in small spatial regions. These processes are sampled with orbiting spacecraft or by fixed ground observatories and so rarely appear in data. Identifying such intervals can be an incredibly time consuming task. We apply a novel, powerful method by which two dimensional data can be automatically processed and embeddings created that contain key features of the data. The distance between embedding vectors serves as a measure of similarity. We apply the state‐of‐the‐art method to two example datasets: MMS electron velocity distributions and auroral all sky images. We show that the technique creates embeddings that group together visually similar observations. When provided with novel example images the method correctly identifies similar intervals: when provided with an electron distribution sampled during an encounter with an electron diffusion region the method recovers similar distributions obtained during two other known diffusion region encounters. Similarly, when provided with an interesting auroral structure the method highlights the same structure observed from an adjacent location and at other close time intervals. The method promises to be a useful tool to expand interesting case studies to multiple events, without requiring manual data labeling. Further, the models could be fine‐tuned with relatively small set of labeled example data to perform tasks such as classification. The embeddings can also be used as input to deep learning models, providing a key intermediary step—capturing the key features within the data.
Commencement and Interruption of Relativistic Electron Dropout in the Heart of the Outer Radiation Belt Induced by a Magnetic Cloud Event
Authors: Wei Jiayun , Zou Zhengyang , Zuo Pingbing , Ni Binbin , Ruan Mengsi , Feng Xueshang
Published: January 2024

We analyze and discuss the commencement and interruption of the relativistic electron dropout in the heart of the outer radiation belt (L* = 4–5) induced by a typical magnetic cloud (MC) event. This MC event impinged the Earth’s magnetosphere on 31 October 2012 and caused a moderate geomagnetic storm with a special prolonged initial phase lasting for >13 hr. The relativistic electrons phase space density (PSD) dropout commenced at L* > 5 during the initial phase. The PSD dropout penetrated deep beyond the heart of the radiation belt (reached L* < 4) at the onset of the main phase, while it was partially enhanced with a local PSD maximum around L* = 4.5, thus causing the interruption of the PSD dropout. The dropout became pronounced at L* > ∼4.7 while the local PSD maximum was maintained throughout the main phase. During the recovery phase, the dropout totally disappeared at L* < 5.5 with relativistic electron PSD gradually recovering to pre‐event level or higher. Further investigations on solar wind parameters and plasma waves give evidence that (a) persistent high dynamic pressure and the triggered Ultra‐Low Frequency waves contribute to the dropout of electrons to interplanetary space during the initial phase and the onset of the main phase; (b) local acceleration by chorus waves during the main phase and recovery phase could explain the interruption of the dropout. Our study underlines the persistent high dynamic pressure competing with intense chorus waves in triggering the commencement and interruption of the relativistic electrons PSD dropout in the heart of the outer radiation belt.
Detecting Cold Pool Family Trees in Convection Resolving Simulations
Authors: Hoeller Jannik , Fiévet Romain , Haerter Jan O.
Published: January 2024

Recent observations and modeling increasingly reveal the key role of cold pools in organizing the convective cloud field. Several methods for detecting cold pools in simulations exist, but are usually based on buoyancy fields and fall short of reliably identifying the active gust front. The current cold pool (CP) detection and tracking algorithm (CoolDeTA), aims to identify cold pools and follow them in time, thereby distinguishing their active gust fronts and the “offspring” rain cells generated nearby. To accomplish these tasks, CoolDeTA utilizes a combination of thermodynamic and dynamical variables and examines the spatial and temporal relationships between cold pools and rain events. We demonstrate that CoolDeTA can reconstruct CP family trees. Using CoolDeTA we can contrast radiative convective equilibrium (RCE) and diurnal cycle CP dynamics, as well as cases with vertical wind shear and without. We show that the results obtained are consistent with a conceptual model where CP triggering of children rain cells follows a simple birth rate, proportional to a CP's gust front length. The proportionality factor depends on the ambient atmospheric stability and is lower for RCE, in line with marginal stability as traditionally ascribed to the moist adiabat. In the diurnal case, where ambient stability is lower, the birth rate thus becomes substantially higher, in line with periodic insolation forcing—resulting in essentially run‐away mesoscale excitations generated by a single parent rain cell and its CP.
AKT2S128/CCTαS315/319/323-positive cancer-associated fibroblasts (CAFs) mediate focal adhesion kinase (FAK) inhibitors resistance via secreting phosphatidylcholines (PCs)
Authors: Chen Jie , Zhang Lingyuan , Zhu Yuheng , Zhao Di , Zhang Jing , Zhu Yanmeng , Pang Jingyuan , Xiao Yuanfan , Wu Qingnan , Wang Yan , Zhan Qimin
Published: January 2024

Abnormal metabolism is regarded as an oncogenic hallmark related to tumor progression and therapeutic resistance. Present study employed multi-omics, including phosphoproteomics, untargeted metabolomics and lipidomics, to demonstrate that the pAKT2 Ser128 and pCCTα Ser315/319/323-positive cancer-associated fibroblasts (CAFs) substantially release phosphatidylcholines (PCs), contributing to the resistance of focal adhesion kinase (FAK) inhibitors in esophageal squamous cell carcinoma (ESCC) treatment. Additionally, we observed extremely low levels of FAK Tyr397 expression in CAFs, potentially offering no available target for FAK inhibitors playing their anti-growth role in CAFs. Consequently, FAK inhibitor increased the intracellular concentration of Ca2+ in CAFs, promoting the formation of AKT2/CCTα complex, leading to phosphorylation of CCTα Ser315/319/323 sites and eventually enhancing stromal PC production. This activation could stimulate the intratumoral Janus kinase 2 (JAK2)/Signal transducer and activator of transcription 3 (STAT3) pathway, triggering resistance to FAK inhibition. Analysis of clinical samples demonstrated that stromal pAKT2 Ser128 and pCCTα Ser315/319/323 are related to the tumor malignancy and reduced patient survival. Pseudo-targeted lipidomics and further validation cohort quantitatively showed that plasma PCs enable to distinguish the malignant extent of ESCC patients. In conclusion, inhibition of stroma-derived PCs and related pathway could be possible therapeutic strategies for tumor therapy.
Safety and efficacy of immune checkpoint inhibitor rechallenge in advanced non-small cell lung cancer: a retrospective study
Authors: Feng Jia , Chen Xinyi , Wei Jiayan , Weng Yiming , Wang Jingsong , Wang Tong , Song Qibin , Min Peng
Published: January 2024

We conducted a retrospective study to evaluate the efficacy of immune checkpoint inhibitor (ICI) rechallenge in patients with advanced non-small cell lung cancer (NSCLC). The study included 111 patients who had previously received ICI therapy and experienced disease progression. The primary endpoints assessed were overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). Our findings revealed that the ICI rechallenge showed promising results in improving patient outcomes. OS (r) is the time from rechallenging with immune checkpoint inhibitors to the last follow-up or death from any cause. The median OS (r) was 14.3 months (95% CI 11.3–17.3 months), with a median PFS (r) of 5.9 months (95% CI 4.1–7.7 months). The ORR was 17.1%; the DCR was 82.3%. Subgroup analysis demonstrated that patients without brain or liver metastases had a longer OS (r) compared to those with metastases (21.6 vs. 13.8 months, χ2 = 3.873, P = 0.046; 20.8 vs. 9.1 months, χ2 = 10.733, P = 0.001, respectively). Moreover, patients without driver gene mutations exhibited significantly longer OS than those with mutations or wild-type patients (22.9 vs. 16.1 vs. 7.5 months, χ2 = 10.710, P = 0.005). Notably, patients who switched to a different ICI during the rechallenge had shorter OS than those who did not change medications (10.4 vs. 21.1 months, χ2 = 9.014, P = 0.003). The incidence of immune-related adverse events did not significantly differ between the two treatment phases. These findings suggest that ICI rechallenge may be a viable therapeutic strategy for select NSCLC patients. Further prospective studies are needed to validate these results and guide treatment decisions for advanced NSCLC.
Dietary supplementation with inulin improves burn-induced skeletal muscle atrophy by regulating gut microbiota disorders
Authors: Gao Shan , Zhao Xiaoshuai , Leng Yan , Xia Zhongyuan
Published: January 2024

Inulin, as a prebiotic, could modulate the gut microbiota. Burn injury leads to gut microbiota disorders and skeletal muscle catabolism. Therefore, whether inulin can improve burn-induced muscle atrophy by regulating microbiota disorders remains unknown. This study aimed to clarify that inulin intake alleviates gut microbiota disorders and skeletal muscle atrophy in burned rats. Rats were divided into the sham group, burn group, prebiotic inulin intervention group, and pseudo-aseptic validation group. A 30% total body surface area (TBSA) third-degree burn wound on dorsal skin was evaluated in all groups except the sham group. Animals in the intervention group received 7 g/L inulin. Animals in the validation group received antibiotic cocktail and inulin treatment. In our study inulin intervention could significantly alleviate the burn-induced skeletal muscle mass decrease and skeletal myoblast cell apoptosis. Inulin intake increased the abundances of Firmicutes and Actinobacteria but decreased the abundance of Proteobacteria. The biosynthesis of amino acids was the most meaningful metabolic pathway distinguishing the inulin intervention group from the burn group, and further mechanistic studies have shown that inulin can promote the phosphorylation of the myogenesis-related proteins PI3K, AKT and P70S6K and activate PI3K/AKT signaling for protein synthesis. In conclusion, inulin alleviated burn induced muscle atrophy through PI3K/AKT signaling and regulated gut microbiota dysbiosis.
Colloidal stability and dielectric behavior of eco-friendly synthesized zinc oxide nanostructures from Moringa seeds
Authors: José Basílio José Augusto , Shinde Mahendra Devidas
Published: January 2024

This study centers on the environmentally benign synthesis of zinc oxide nanoparticles (ZnO NPs) derived from Zn (CH3COO)2·2H2O and Moringa seeds. The synthesized nanostructures underwent comprehensive characterization utilizing diverse analytical techniques, encompassing X-ray diffraction (XRD), UV–VIS spectroscopy, field-emission scanning electron microscopy (FESEM), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy. XRD measurements coupled with W–H plot transformation unequivocally confirmed the formation of ZnO nanostructures, characterized by an average size of 24.9 nm. UV–VIS spectroscopy, complemented by Kubelka Munk curve analysis, elucidated the direct conduction and determined a bandgap of 3.265 eV. FESEM analysis revealed minimal particle aggregation, showcasing well-defined grain boundaries spanning sizes from 20.4 to 87.7 nm. XPS analysis substantiated the presence of Zn (2p), Zn (3p), Zn (3d), and O (1s). Raman spectroscopy identified E2H as the predominant mode, followed by E1(TO) and (E2H-E2L). ZnO thin films, fabricated via pulsed laser deposition (PLD) and deposited onto silicon (100) substrates, exhibited exemplary morphology and discernible topography, characterized by a normal grain size distribution. Zeta potential tests yielded a value of approximately ($$\mathcalligra{z}$$
z
~ − 43.8 mV), indicative of the commendable stability of the colloidal suspension, likely attributable to low particle aggregation. Dielectric measurements conducted on sintered pellets at 900 °C unveiled elevated capacitance and dielectric constant at low frequencies across the temperature range of 289.935–310 K. These findings affirm the potential utility of environmentally synthesized ZnO for a spectrum of applications, including energy devices and nanofluids.
Characterization of CD90/Thy-1 as a crucial molecular signature for myogenic differentiation in human urine-derived cells through single-cell RNA sequencing
Authors: Kunitake Katsuhiko , Motohashi Norio , Inoue Takafumi , Suzuki Yutaka , Aoki Yoshitsugu
Published: January 2024

Human urine-derived cells (UDCs) are primary cultured cells originating from the upper urinary tract and are known to be multipotent. We previously developed MYOD1-transduced UDCs (MYOD1-UDCs) as a model recapitulating the pathogenesis of Duchenne muscular dystrophy (DMD) caused by a lack of dystrophin. MYOD1-UDCs also allow evaluation of the efficacy of exon skipping with antisense oligonucleotides. However, despite the introduction of MYOD1, some MYOD1-UDCs failed to form myotubes, possibly because of heterogeneity among UDCs. Here, we carried out single-cell RNA-sequencing analyses and revealed that CD90/Thy-1 was highly expressed in a limited subpopulation of UDCs with high myogenic potency. Furthermore, CD90-positive MYOD1-UDCs, but not CD90-negative cells, could form myotubes expressing high levels of myosin heavy chain and dystrophin. Notably, overexpression of CD90 in CD90-negative MYOD1-UDCs did not enhance myogenic differentiation, whereas CD90 suppression in CD90-positive UDCs led to decreased myotube formation and decreased myosin heavy chain expression. CD90 may thus contribute to the fusion of single-nucleated MYOD1-UDCs into myotubes but is not crucial for promoting the expression of late muscle regulatory factors. Finally, we confirmed that CD90-positive MYOD1-UDCs derived from patients with DMD were a valuable tool for obtaining a highly reproducible and stable evaluation of exon skipping using antisense oligonucleotide.
Photocatalytic activity of the biogenic mediated green synthesized CuO nanoparticles confined into MgAl LDH matrix
Authors: Berede Hildana Tesfaye , Andoshe Dinsefa Mensur , Gultom Noto Susanto , Kuo Dong-Hau , Chen Xiaoyun , Abdullah Hairus , Wondimu Tadele Hunde , Wu Yi-nan , Zelekew Osman Ahmed
Published: January 2024

The global concern over water pollution caused by organic pollutants such as methylene blue (MB) and other dyes has reached a critical level. Herein, the Allium cepa L. peel extract was utilized to fabricate copper oxide (CuO) nanoparticles. The CuO was combined with MgAl-layered double hydroxides (MgAl-LDHs) via a co-precipitation method with varying weight ratios of the CuO/LDHs. The composite catalysts were characterized and tested for the degradation of MB dye. The CuO/MgAl-LDH (1:2) showed the highest photocatalytic performance and achieved 99.20% MB degradation. However, only 90.03, 85.30, 71.87, and 35.53% MB dye was degraded with CuO/MgAl-LDHs (1:1), CuO/MgAl-LDHs (2:1), CuO, and MgAl-LDHs catalysts, respectively. Furthermore, a pseudo-first-order rate constant of the CuO/MgAl-LDHs (1:2) was 0.03141 min−1 while the rate constants for CuO and MgAl-LDHs were 0.0156 and 0.0052 min−1, respectively. The results demonstrated that the composite catalysts exhibited an improved catalytic performance than the pristine CuO and MgAl-LDHs. The higher photocatalytic performances of composite catalysts may be due to the uniform distribution of CuO nanoparticles into the LDH matrix, the higher surface area, and the lower electron and hole recombination rates. Therefore, the CuO/MgAl-LDHs composite catalyst can be one of the candidates used in environmental remediation.
Prognostic and immune predictive roles of a novel tricarboxylic acid cycle-based model in hepatocellular carcinoma
Authors: Zeng Yifan , Yu Tao , Jiang Shuwen , Wang Jinzhi , Chen Lin , Lou Zhuoqi , Pan Liya , Zhang Yongtao , Ruan Bing
Published: January 2024

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer. Since the tricarboxylic acid cycle is widely involved in tumor metabolic reprogramming and cuproptosis, investigating related genes may help to identify prognostic signature of patients with HCC. Data on patients with HCC were sourced from public datasets, and were divided into train, test, and single-cell cohorts. A variety of machine learning algorithms were used to identify different molecular subtypes and determine the prognostic risk model. Our findings revealed that the risk score (TRscore), based on the genes OGDHL, CFHR4, and SPP1, showed excellent predictive performance in different datasets. Pathways related to cell cycle and immune inflammation were enriched in the high-risk group, whereas metabolism-related pathways were significantly enriched in the low-risk group. The high-risk group was associated with a greater number of mutations of detrimental biological behavior and higher levels of immune infiltration, immune checkpoint expression, and anti-cancer immunotherapy response. Low-risk patients demonstrated greater sensitivity to erlotinib and phenformin. SPP1 was mainly involved in the interaction among tumor-associated macrophages, T cells, and malignant cells via SPP1–CD44 and SPP1–(ITGA5 + ITGB1) ligand-receptor pairs. In summary, our study established a prognostic model, which may contribute to individualized treatment and clinical management of patients with HCC.
Response score-based protein structure analysis for cancer prediction aided by the Internet of Things
Authors: Alruwaili Omar , Yousef Amr , Jumani Touqeer A. , Armghan Ammar
Published: January 2024

Medical diagnosis through prediction and analysis is par excellence in integrating modern technologies such as the Internet of Things (IoT). With the aid of such technologies, clinical assessments are eased with protracted computing. Specifically, cancer research through structure prediction and analysis is improved through human and machine interventions sustaining precision improvements. This article, therefore, introduces a Protein Structure Prediction Technique based on Three-Dimensional Sequence. This sequence is modeled using amino acids and their folds observed during the pre-initial cancer stages. The observed sequences and the inflammatory response score of the structure are used to predict the impact of cancer. In this process, ensemble learning is used to identify sequence and folding responses to improve inflammations. This score is correlated with the clinical data for structures and their folds independently for determining the structure changes. Such changes through different sequences are handled using repeated ensemble learning for matching and unmatching response scores. The introduced idea integrated with deep ensemble learning and IoT combination, notably employing stacking method for enhanced cancer prediction precision and interdisciplinary collaboration. The proposed technique improves prediction precision, data correlation, and change detection by 11.83%, 8.48%, and 13.23%, respectively. This technique reduces correlation time and complexity by 10.43% and 12.33%, respectively.
Next generation phenotyping for diagnosis and phenotype–genotype correlations in Kabuki syndrome
Authors: Hennocq Quentin , Willems Marjolaine , Amiel Jeanne , Arpin Stéphanie , Attie-Bitach Tania , Bongibault Thomas , Bouygues Thomas , Cormier-Daire Valérie , Corre Pierre , Dieterich Klaus , Douillet Maxime , Feydy Jean , Galliani Eva , Giuliano Fabienne , Lyonnet Stanislas , Picard Arnaud , Porntaveetus Thantrira , Rio Marlène , Rouxel Flavien , Shotelersuk Vorasuk , Toutain Annick , Yauy Kevin , Geneviève David , Khonsari Roman H. , Garcelon Nicolas
Published: January 2024

The field of dysmorphology has been changed by the use Artificial Intelligence (AI) and the development of Next Generation Phenotyping (NGP). The aim of this study was to propose a new NGP model for predicting KS (Kabuki Syndrome) on 2D facial photographs and distinguish KS1 (KS type 1, KMT2D-related) from KS2 (KS type 2, KDM6A-related). We included retrospectively and prospectively, from 1998 to 2023, all frontal and lateral pictures of patients with a molecular confirmation of KS. After automatic preprocessing, we extracted geometric and textural features. After incorporation of age, gender, and ethnicity, we used XGboost (eXtreme Gradient Boosting), a supervised machine learning classifier. The model was tested on an independent validation set. Finally, we compared the performances of our model with DeepGestalt (Face2Gene). The study included 1448 frontal and lateral facial photographs from 6 centers, corresponding to 634 patients (527 controls, 107 KS); 82 (78%) of KS patients had a variation in the KMT2D gene (KS1) and 23 (22%) in the KDM6A gene (KS2). We were able to distinguish KS from controls in the independent validation group with an accuracy of 95.8% (78.9–99.9%, p < 0.001) and distinguish KS1 from KS2 with an empirical Area Under the Curve (AUC) of 0.805 (0.729–0.880, p < 0.001). We report an automatic detection model for KS with high performances (AUC 0.993 and accuracy 95.8%). We were able to distinguish patients with KS1 from KS2, with an AUC of 0.805. These results outperform the current commercial AI-based solutions and expert clinicians.
Identifying the need for infection-related consultations in intensive care patients using machine learning models
Authors: Zwerwer Leslie R. , Luz Christian F. , Soudis Dimitrios , Giudice Nicoletta , Nijsten Maarten W. N. , Glasner Corinna , Renes Maurits H. , Sinha Bhanu
Published: January 2024

Infection-related consultations on intensive care units (ICU) have a positive impact on quality of care and clinical outcome. However, timing of these consultations is essential and to date they are typically event-triggered and reactive. Here, we investigate a proactive approach to identify patients in need for infection-related consultations by machine learning models using routine electronic health records. Data was retrieved from a mixed ICU at a large academic tertiary care hospital including 9684 admissions. Infection-related consultations were predicted using logistic regression, random forest, gradient boosting machines, and long short-term memory neural networks (LSTM). Overall, 7.8% of admitted patients received an infection-related consultation. Time-sensitive modelling approaches performed better than static approaches. Using LSTM resulted in the prediction of infection-related consultations in the next clinical shift (up to eight hours in advance) with an area under the receiver operating curve (AUROC) of 0.921 and an area under the precision recall curve (AUPRC) of 0.541. The successful prediction of infection-related consultations for ICU patients was done without the use of classical triggers, such as (interim) microbiology reports. Predicting this key event can potentially streamline ICU and consultant workflows and improve care as well as outcome for critically ill patients with (suspected) infections.
Path planning in three-dimensional space based on butterfly optimization algorithm
Authors: Mazaheri Hakimeh , Goli Salman , Nourollah Ali
Published: January 2024

Path planning is one of the most critical issues in many related fields including UAVs. Many researchers have addressed this problem according to different conditions and limitations, but modelling the 3-D space and routing with an evolutional algorithm in such spaces is an open issue. So, in this paper, we first, introduce a method to grids the environment using geometrical shapes. This can reduce the random states of cell decomposition and increases the computational speed. We then propose an effective routing algorithm based on the butterfly optimization algorithm (BOA). It can simultaneously optimize multiple path planning objectives. It uses an objective function to compute the shortest path, based on obstacle avoidance and the UAV’s operational power minimization. A novel concept, the intelligent throwing agent, used in this algorithm prevents getting stuck in local optima and increases the network coverage in path planning. The throwing agent prevents the collision of the UAV with the obstacles using geometrical techniques and contour lines. The simulation results show that BOA has the least and second-least cost in best-case and worst-case scenarios in comparison with ant colony and particle swarm. Its run time and the optimal value of the fitting function are also better than the two other algorithms.