bluuebunny/crossref_metadata_2025 huggingface dataset:
Anomalous enhancement of charge density wave in kagome superconductor CsV3Sb5 approaching the 2D limit
Authors: Song Boqin , Ying Tianping , Wu Xianxin , Xia Wei , Yin Qiangwei , Zhang Qinghua , Song Yanpeng , Yang Xiaofan , Guo Jiangang , Gu Lin , Chen Xiaolong , Hu Jiangping , Schnyder Andreas P. , Lei Hechang , Guo Yanfeng , Li Shiyan
Published: April 2023

The recently discovered kagome metals AV3Sb5 (A = Cs, Rb, K) exhibit a variety of intriguing phenomena, such as a charge density wave (CDW) with time-reversal symmetry breaking and possible unconventional superconductivity. Here, we report a rare non-monotonic evolution of the CDW temperature (TCDW) with the reduction of flake thickness approaching the atomic limit, and the superconducting transition temperature (Tc) features an inverse variation with TCDW. TCDW initially decreases to a minimum value of 72 K at 27 layers and then increases abruptly, reaching a record-high value of 120 K at 5 layers. Raman scattering measurements reveal a weakened electron-phonon coupling with the reduction of sample thickness, suggesting that a crossover from electron-phonon coupling to dominantly electronic interactions could account for the non-monotonic thickness dependence of TCDW. Our work demonstrates the novel effects of dimension reduction and carrier doping on quantum states in thin flakes and provides crucial insights into the complex mechanism of the CDW order in the family of AV3Sb5 kagome metals.
Regulating the electronic structure through charge redistribution in dense single-atom catalysts for enhanced alkene epoxidation
Authors: Jin Hongqiang , Zhou Kaixin , Zhang Ruoxi , Cui Hongjie , Yu Yu , Cui Peixin , Song Weiguo , Cao Changyan
Published: April 2023

Inter-site interaction in densely populated single-atom catalysts has been demonstrated to have a crucial role in regulating the electronic structure of metal atoms, and consequently their catalytic performances. We herein report a general and facile strategy for the synthesis of several densely populated single-atom catalysts. Taking cobalt as an example, we further produce a series of Co single-atom catalysts with varying loadings to investigate the influence of density on regulating the electronic structure and catalytic performance in alkene epoxidation with O2. Interestingly, the turnover frequency and mass-specific activity are significantly enhanced by 10 times and 30 times with increasing Co loading from 5.4 wt% to 21.2 wt% in trans-stilbene epoxidation, respectively. Further theoretical studies reveal that the electronic structure of densely populated Co atoms is altered through charge redistribution, resulting in less Bader charger and higher d-band center, which are demonstrated to be more beneficial for the activation of O2and trans-stilbene. The present study demonstrates a new finding about the site interaction in densely populated single-atom catalysts, shedding insight on how density affects the electronic structure and catalytic performance for alkene epoxidation.
Psychological proximity improves reasoning in academic aptitude tests
Authors: Hadar Britt , Katzir Maayan , Pumpian Sephi , Karelitz Tzur , Liberman Nira
Published: April 2023

Performance on standardized academic aptitude tests (AAT) can determine important life outcomes. However, it is not clear whether and which aspects of the content of test questions affect performance. We examined the effect of psychological distance embedded in test questions. In Study 1 (N = 41,209), we classified the content of existing AAT questions as invoking proximal versus distal details. We found better performance with proximal compared to distal questions, especially for low-achieving examinees. Studies 2 and 3 manipulated the distance of questions adapted from AATs and examined three moderators: overall AAT score, working-memory capacity, and presence of irrelevant information. In Study 2 (N = 129), proximity (versus distance) improved the performance of low-achieving participants. In Study 3 (N = 1744), a field study, among low-achieving examinees, proximity improved performance on questions that included irrelevant information. Together, these results suggest that the psychological distance that is invoked by the content of test questions has important consequences for performance in real-life high-stakes tests.
Bifurcation analysis of hepatitis B virus with non-cytolytic cure process on infected liver and blood cells
Authors: Mamo Tesfaye Tefera
Published: April 2023

The phenomenon of bifurcation in disease transmission models has been observed in a number of epidemiological models. The consequence of bifurcation is that the classical requirement of the reproduction number being less than unity becomes only a necessary, but not sufficient, for disease elimination. This paper addresses the problem of finding the causes of bifurcation in standard deterministic models for the spread of HBV diseases with non-Cytolytic cure processes on infected liver and blood cells. The model contains logistic growth of healthy liver and blood cells and non -Cytolytic cure processes of infected cells. I have got that the model exhibits back ward and forward bifurcations with some conditions. The existence of a backward bifurcation is an interesting artifact since this means that the disease cannot be eradicated by simply reducing the value of the basic reproduction number$${R}_{0}$$R0below 1.This can have important implications on drug therapy protocols, since it sheds light on possible control mechanisms for disease eradication.
Comparison of postoperative outcomes between bikini-incision via direct anterior approach and posterolateral approach in simultaneous bilateral total hip arthroplasty: a randomized controlled trial
Authors: Jin Xin , Chen Guo , Chen Mengcun , Riaz Muhammad N. , Wang Jing , Yang Shuhua , Xu Weihua
Published: April 2023

The purpose of this study was to compare an oblique bikini-incision via direct anterior approach (BI-DAA) to a conventional posterolateral approach (PLA) during simultaneous bilateral total hip arthroplasty (simBTHA) in terms of early patient outcomes, postoperative functional recovery, and complications. From January 2017 to January 2020, 106 patients receiving simBTHA were enrolled and randomly allocated to the BI-DAA or PLA group. Primary outcomes were measured using hemoglobin (HGB) drop, transfusion rate, the length of stay (LOS), the visual analog scale (VAS) for pain, the Harris hip score, Western Ontario and McMaster Universities Osteoarthritis Index, and the scar cosmesis assessment and rating scale. Secondary outcomes were the operative time, radiographic measurements, including femoral offset, femoral anteversion, stem varus/valgus angle, and leg length discrepancy (LLD). The occurrence of postoperative complications was also recorded. There were no differences in demographic or clinical characteristics before surgery. Compared to the PLA, the patients in the BI-DAA group had lower HGB drop (24.7 ± 13.3 g/L vs. 34.7 ± 16.7, P < .01) and transfusion rates (9/50 vs. 18/50, P = .04) and a shorter LOS (5.12 ± 1.5 vs. 6.40 ± 2.0 days, P < .01) without increasing the operative time (169.7 ± 17.3 vs. 167.5 ± 21.8 min, P = .58). The BI-DAA group yielded a smaller LLD (2.1 ± 2.3 vs. 3.8 ± 3.0 mm, P < .01) and less variability in component orientation than the PLA group (100% vs. 93%, P = .01). As for the scar, the BI-DAA group produced a shorter incision length (9.7 ± 1.6 vs. 10.8 ± 2.0 mm, P < .01) and higher postoperative recovery satisfaction than the PLA group. Furthermore, the BI-DAA group had a reduced VAS score one week after surgery and had better functional recovery in three months postoperatively. The BI-DAA group had a higher incidence of LFCN dysesthesia (12/100 vs. 0/100 thighs, P < .01), while other complications did not differ significantly between the two groups. For simBTHA, the bikini incision offers early recovery, less variance in components orientation, better postoperative outcomes, and scar healing than the PLA. Therefore, the bikini incision could be a safe and feasible option for simBTHA recipients.
Personalized prediction of one-year mental health deterioration using adaptive learning algorithms: a multicenter breast cancer prospective study
Authors: Kourou Konstantina , Manikis Georgios , Mylona Eugenia , Poikonen-Saksela Paula , Mazzocco Ketti , Pat-Horenczyk Ruth , Sousa Berta , Oliveira-Maia Albino J. , Mattson Johanna , Roziner Ilan , Pettini Greta , Kondylakis Haridimos , Marias Kostas , Nuutinen Mikko , Karademas Evangelos , Simos Panagiotis , Fotiadis Dimitrios I.
Published: April 2023

Identifying individual patient characteristics that contribute to long-term mental health deterioration following diagnosis of breast cancer (BC) is critical in clinical practice. The present study employed a supervised machine learning pipeline to address this issue in a subset of data from a prospective, multinational cohort of women diagnosed with stage I–III BC with a curative treatment intention. Patients were classified as displaying stable HADS scores (Stable Group; n = 328) or reporting a significant increase in symptomatology between BC diagnosis and 12 months later (Deteriorated Group; n = 50). Sociodemographic, life-style, psychosocial, and medical variables collected on the first visit to their oncologist and three months later served as potential predictors of patient risk stratification. The flexible and comprehensive machine learning (ML) pipeline used entailed feature selection, model training, validation and testing. Model-agnostic analyses aided interpretation of model results at the variable- and patient-level. The two groups were discriminated with a high degree of accuracy (Area Under the Curve = 0.864) and a fair balance of sensitivity (0.85) and specificity (0.87). Both psychological (negative affect, certain coping with cancer reactions, lack of sense of control/positive expectations, and difficulties in regulating negative emotions) and biological variables (baseline percentage of neutrophils, thrombocyte count) emerged as important predictors of mental health deterioration in the long run. Personalized break-down profiles revealed the relative impact of specific variables toward successful model predictions for each patient. Identifying key risk factors for mental health deterioration is an essential first step toward prevention. Supervised ML models may guide clinical recommendations toward successful illness adaptation.
The $$^{1}\!S_{0}$$ channel of proton–proton scattering in new chiral effective field theory power counting
Authors: Behzadmoghaddam B. , Radin M. , Bayegan S.
Published: April 2023

In this paper, the chiral effective field theory is used to investigate the spin singlet channel $$^{1\!}S_{0}$$

1

S
0

, of proton-proton (pp) scattering according to the new suggested power counting. For this purpose, the pp zero scattering amplitude is reproduced by inserting one pion exchange at leading order (LO) and the Coulomb interaction between protons at next-to-leading order (NLO). This leads to a systematic improvement up to NLO compared to the result obtained from Nijm93 potential model.
mTORC2 interactome and localization determine aggressiveness of high-grade glioma cells through association with gelsolin
Authors: Chantaravisoot Naphat , Wongkongkathep Piriya , Kalpongnukul Nuttiya , Pacharakullanon Narawit , Kaewsapsak Pornchai , Ariyachet Chaiyaboot , Loo Joseph A. , Tamanoi Fuyuhiko , Pisitkun Trairak
Published: April 2023

mTOR complex 2 (mTORC2) has been implicated as a key regulator of glioblastoma cell migration. However, the roles of mTORC2 in the migrational control process have not been entirely elucidated. Here, we elaborate that active mTORC2 is crucial for GBM cell motility. Inhibition of mTORC2 impaired cell movement and negatively affected microfilament and microtubule functions. We also aimed to characterize important players involved in the regulation of cell migration and other mTORC2-mediated cellular processes in GBM cells. Therefore, we quantitatively characterized the alteration of the mTORC2 interactome under selective conditions using affinity purification-mass spectrometry in glioblastoma. We demonstrated that changes in cell migration ability specifically altered mTORC2-associated proteins. GSN was identified as one of the most dynamic proteins. The mTORC2-GSN linkage was mostly highlighted in high-grade glioma cells, connecting functional mTORC2 to multiple proteins responsible for directional cell movement in GBM. Loss of GSN disconnected mTORC2 from numerous cytoskeletal proteins and affected the membrane localization of mTORC2. In addition, we reported 86 stable mTORC2-interacting proteins involved in diverse molecular functions, predominantly cytoskeletal remodeling, in GBM. Our findings might help expand future opportunities for predicting the highly migratory phenotype of brain cancers in clinical investigations.
Enriched environment exposure during development positively impacts the structure and function of the visual cortex in mice
Authors: Bibollet-Bahena O. , Tissier S. , Ho-Tran S. , Rojewski A. , Casanova C.
Published: April 2023

Optimal conditions of development have been of interest for decades, since genetics alone cannot fully explain how an individual matures. In the present study, we used optical brain imaging to investigate whether a relatively simple enrichment can positively influence the development of the visual cortex of mice. The enrichment paradigm was composed of larger cages housing multiple mice that contained several toys, hiding places, nesting material and a spinning wheel that were moved or replaced at regular intervals. We compared C57BL/6N adult mice (> P60) that had been raised either in an enriched environment (EE; n = 16) or a standard (ST; n = 12) environment from 1 week before birth to adulthood, encompassing all cortical developmental stages. Here, we report significant beneficial changes on the structure and function of the visual cortex following environmental enrichment throughout the lifespan. More specifically, retinotopic mapping through intrinsic signal optical imaging revealed that the size of the primary visual cortex was greater in mice reared in an EE compared to controls. In addition, the visual field coverage of EE mice was wider. Finally, the organization of the cortical representation of the visual field (as determined by cortical magnification) versus its eccentricity also differed between the two groups. We did not observe any significant differences between females and males within each group. Taken together, these data demonstrate specific benefits of an EE throughout development on the visual cortex, which suggests adaptation to their environmental realities.
Investigating the association between glycaemic traits and colorectal cancer in the Japanese population using Mendelian randomisation
Authors: Hanyuda Akiko , Goto Atsushi , Katagiri Ryoko , Koyanagi Yuriko N. , Nakatochi Masahiro , Sutoh Yoichi , Nakano Shiori , Oze Isao , Ito Hidemi , Yamaji Taiki , Sawada Norie , Iwagami Masao , Kadota Aya , Koyama Teruhide , Katsuura-Kamano Sakurako , Ikezaki Hiroaki , Tanaka Keitaro , Takezaki Toshiro , Imoto Issei , Suzuki Midori , Momozawa Yukihide , Takeuchi Kenji , Narita Akira , Hozawa Atsushi , Kinoshita Kengo , Shimizu Atsushi , Tanno Kozo , Matsuo Keitaro , Tsugane Shoichiro , Wakai Kenji , Sasaki Makoto , Yamamoto Masayuki , Iwasaki Motoki
Published: April 2023

Observational studies suggest that abnormal glucose metabolism and insulin resistance contribute to colorectal cancer; however, the causal association remains unknown, particularly in Asian populations. A two-sample Mendelian randomisation analysis was performed to determine the causal association between genetic variants associated with elevated fasting glucose, haemoglobin A1c (HbA1c), and fasting C-peptide and colorectal cancer risk. In the single nucleotide polymorphism (SNP)-exposure analysis, we meta-analysed study-level genome-wide associations of fasting glucose (~ 17,289 individuals), HbA1c (~ 52,802 individuals), and fasting C-peptide (1,666 individuals) levels from the Japanese Consortium of Genetic Epidemiology studies. The odds ratios of colorectal cancer were 1.01 (95% confidence interval [CI], 0.99–1.04, P = 0.34) for fasting glucose (per 1 mg/dL increment), 1.02 (95% CI, 0.60–1.73, P = 0.95) for HbA1c (per 1% increment), and 1.47 (95% CI, 0.97–2.24, P = 0.06) for fasting C-peptide (per 1 log increment). Sensitivity analyses, including Mendelian randomisation-Egger and weighted-median approaches, revealed no significant association between glycaemic characteristics and colorectal cancer (P > 0.20). In this study, genetically predicted glycaemic characteristics were not significantly related to colorectal cancer risk. The potential association between insulin resistance and colorectal cancer should be validated in further studies.
Human health-risk assessment of heavy metal–contaminated soil based on Monte Carlo simulation
Authors: Panqing Ye , Abliz Abdugheni , Xiaoli Sun , Aisaiduli Halidan
Published: April 2023

Soil contamination soils of by heavy metals (HMs) poses serious threats to the soil environment and enters the human body through exposure pathways such as ingestion and skin contact, posing a threat to human health. The purpose of this study was to analyze the sources and contributions of soil HMs, and to quantitatively assess the human health risks of soil HMs to different populations (i.e. children, adult females and adult males), and to analyze the human health risks caused by various sources of sensitive populations. 170 topsoil (0–20 cm) were collected from Fukang, Jimsar and Qitai on the northern slope of Tianshan Mountains in Xinjiang, China, and the contents of Zn, Cu, Cr, Pb and Hg were determined. This study used the Unmix model and a health-risk assessment (HRA) model to assess the human health risks of five HMs. The results showed that: (1) The mean values of Zn and Cr were lower than the background values of Xinjiang, the mean values of Cu and Pb were slightly higher than the background values of Xinjiang but lower than the national standard, and the mean value of Hg and Pb was higher than the background value of Xinjiang and the national standard. (2) The sources of soil HMs in the region were mainly traffic, natural, coal, and industrial sources. Moreover, the HRA model combined with Monte Carlo simulation showed similar trends in the health-risk status of all population groups in the region. Probabilistic HRA revealed that noncarcinogenic risks were acceptable for all populations (HI < 1) while carcinogenic risks were high (children: 77.52%; female: 69.09%; male: 65.63%). For children, carcinogenic risk from industrial and coal sources exceeded the acceptable threshold by 2.35 and 1.20 times, respectively, and Cr was the main element contributing to human carcinogenic risk. These findings suggest that carcinogenic risks from coal-based Cr emissions cannot be ignored, and the study area should aim to control Cr emissions from industrial sources. The results of this study provide support for the prevention of human health risks and the control of soil HMs pollution across different age groups.
Powder metallurgy as a perfect technique for preparation of Cu–TiO2 composite by identifying their microstructure and optical properties
Authors: Eessaa Ashraf K. , Elkady Omayma A. , El-Shamy A. M.
Published: April 2023

Powder metallurgy (PM) is a technique that involves the manufacturing of metal powders and their consolidation into finished products or components. This process involves the mixing of metal powders with other materials such as ceramics or polymers, followed by the application of heat and pressure to produce a solid, dense material. The use of PM has several advantages over traditional manufacturing techniques, including the ability to create complex shapes and the production of materials with improved properties. Cu–TiO2 composite materials are of great interest due to their unique properties, such as high electrical conductivity, improved mechanical strength, and enhanced catalytic activity. The synthesis of Cu–TiO2 composites using the PM technique has been gaining popularity in recent years due to its simplicity, cost-effectiveness, and ability to produce materials with excellent homogeneity. The novelty of using the PM technique for the preparation of Cu–TiO2 composite lies in the fact that it enables the production of materials with controlled microstructures and optical properties. The microstructure of the composite can be fine-tuned by controlling the particle size and distribution of the starting powders, as well as the processing parameters such as temperature, pressure, and sintering time. The optical properties of the composite can also be tailored by adjusting the size and distribution of the TiO2 particles, which can be used to control the absorption and scattering of light. This makes Cu–TiO2 composites particularly useful for applications such as photocatalysis and solar energy conversion. In summary, the use of Powder Metallurgy for the preparation of Cu–TiO2 composite is a novel and effective technique for producing materials with controlled microstructures and optical properties. The unique properties of Cu–TiO2 composites make them attractive for a wide range of applications in various fields, including energy, catalysis, and electronics.
Identification and validation of fatty acid metabolism-related lncRNA signatures as a novel prognostic model for clear cell renal cell carcinoma
Authors: Shen Cheng , Chen Zhan , Jiang Jie , Zhang Yong , Chen Xinfeng , Xu Wei , Peng Rui , Zuo Wenjing , Jiang Qian , Fan Yihui , Fang Xingxing , Zheng Bing
Published: April 2023

Clear cell renal cell carcinoma (ccRCC) is a main subtype of renal cancer, and advanced ccRCC frequently has poor prognosis. Many studies have found that lipid metabolism influences tumor development and treatment. This study was to examine the prognostic and functional significance of genes associated with lipid metabolism in individuals with ccRCC. Using the database TCGA, differentially expressed genes (DEGs) associated with fatty acid metabolism (FAM) were identified. Prognostic risk score models for genes related to FAM were created using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Our findings demonstrate that the prognosis of patients with ccRCC correlate highly with the profiles of FAM-related lncRNAs (AC009166.1, LINC00605, LINC01615, HOXA-AS2, AC103706.1, AC009686.2, AL590094.1, AC093278.2). The prognostic signature can serve as an independent predictive predictor for patients with ccRCC. The predictive signature's diagnostic effectiveness was superior to individual clinicopathological factors. Between the low- and high-risk groups, immunity research revealed a startling difference in terms of cells, function, and checkpoint scores. Chemotherapeutic medications such lapatinib, AZD8055, and WIKI4 had better outcomes for patients in the high-risk group. Overall, the predictive signature can help with clinical selection of immunotherapeutic regimens and chemotherapeutic drugs, improving prognosis prediction for ccRCC patients.
Dietary phytochemical index is favorably associated with oxidative stress status and cardiovascular risk factors in adults with obesity
Authors: Hamedi-Shahraki Soudabeh , Jowshan Mohammad-Reza , Zolghadrpour Mohammad-Amin , Amirkhizi Farshad , Asghari Somayyeh
Published: April 2023

Phytochemicals are bioactive compounds found in plant-based foods. Consumption of phytochemical-rich foods has been associated with cardiovascular and metabolic diseases prevention in various populations. To quantify the phytochemical content of the diet, dietary phytochemical index (DPI) was established which is defined as the proportion of daily energy intake derived from foods rich in phytochemicals. The purpose of this study was to evaluate the association between the DPI and oxidative stress markers and cardiovascular risk factors in obese adults. In this cross-sectional study, a total of 140 adults aged 20–60 years and body mass index (BMI) of ≥ 30 kg/m2 were included. A validated food frequency questionnaire (FFQ) was used to collect information on dietary intakes. The DPI was calculated based on the following formula: DPI = [daily energy obtained from foods rich in phytochemicals (kcal)/total daily energy intake (kcal) × 100]. There was an inverse association between DPI and serum concentrations of Malondialdehyde (MDA) (P = 0.004), triglyceride (TG) (P-trend = 0.003), high-sensitive C-reactive protein (hs-CRP) (P = 0.017), and erythrocyte superoxide dismutase (SOD) activity (P = 0.024). Total antioxidant capacity (TAC) was positively associated with DPI score (P = 0.045). No significant relationship was found between the DPI score and fasting blood sugar (FBS), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total oxidant status (TOS), glutathione peroxidase (GPx), catalase (CAT), and anthropometric parameters as well as systolic and diastolic blood pressure. The current study found that there was a significant inverse association between DPI and oxidative stress, inflammation, and hypertriglyceridemia as cardiovascular disease (CVD) risk factors in obese population. However, further research is needed to confirm these findings.
Short-term inflow forecasting in a dam-regulated river in Southwest Norway using causal variational mode decomposition
Authors: Yousefi Mojtaba , Wang Jinghao , Fandrem Høivik Øivind , Rajasekharan Jayaprakash , Hubert Wierling August , Farahmand Hossein , Arghandeh Reza
Published: April 2023

Climate change affects patterns and uncertainties associated with river water regimes, which significantly impact hydropower generation and reservoir storage operation. Hence, reliable and accurate short-term inflow forecasting is vital to face climate effects better and improve hydropower scheduling performance. This paper proposes a Causal Variational Mode Decomposition (CVD) preprocessing framework for the inflow forecasting problem. CVD is a preprocessing feature selection framework that is built upon multiresolution analysis and causal inference. CVD can reduce computation time while increasing forecasting accuracy by down-selecting the most relevant features to the target value (inflow in a specific location). Moreover, the proposed CVD framework is a complementary step to any machine learning-based forecasting method as it is tested with four different forecasting algorithms in this paper. CVD is validated using actual data from a river system downstream of a hydropower reservoir in the southwest of Norway. The experimental results show that CVD-LSTM reduces forecasting error metric by almost 70% compared with a baseline (scenario 1) and reduces by 25% compared to an LSTM for the same composition of input data (scenario 4).
Content-based filter queries on DNA data storage systems
Authors: El-Shaikh Alex , Seeger Bernhard
Published: April 2023

Recent developments in DNA data storage systems have revealed the great potential to store large amounts of data at a very high density with extremely long persistence and low cost. However, despite recent contributions to robust data encoding, current DNA storage systems offer limited support for random access on DNA storage devices due to restrictive biochemical constraints. Moreover, state-of-the-art approaches do not support content-based filter queries on DNA storage. This paper introduces the first encoding for DNA that enables content-based searches on structured data like relational database tables. We provide the details of the methods for coding and decoding millions of directly accessible data objects on DNA. We evaluate the derived codes on real data sets and verify their robustness.
Reward maximization assessed using a sequential patch depletion task in a large sample of heterogeneous stock rats
Authors: Gancarz Amy M. , Mitchell Suzanne H. , George Anthony M. , Martin Connor D. , Turk Marisa C. , Bool Heather M. , Aktar Fahmida , Kwarteng Francis , Palmer Abraham A. , Meyer Paul J. , Richards Jerry B. , Dietz David M. , Ishiwari Keita
Published: April 2023

Choice behavior requires animals to evaluate both short- and long-term advantages and disadvantages of all potential alternatives. Impulsive choice is traditionally measured in laboratory tasks by utilizing delay discounting (DD), a paradigm that offers a choice between a smaller immediate reward, or a larger more delayed reward. This study tested a large sample of Heterogeneous Stock (HS) male (n = 896) and female (n = 898) rats, part of a larger genetic study, to investigate whether measures of reward maximization overlapped with traditional models of delay discounting via the patch depletion model using a Sequential Patch Depletion procedure. In this task, rats were offered a concurrent choice between two water “patches” and could elect to “stay” in the current patch or “leave” for an alternative patch. Staying in the current patch resulted in decreasing subsequent reward magnitudes, whereas the choice to leave a patch was followed by a delay and a resetting to the maximum reward magnitude. Based on the delay in a given session, different visit durations were necessary to obtain the maximum number of rewards. Visit duration may be analogous to an indifference point in traditional DD tasks. Males and females did not significantly differ on traditional measures of DD (e.g. delay gradient; AUC). When examining measures of patch utilization, females made fewer patch changes at all delays and spent more time in the patch before leaving for the alternative patch compared to males. Consistent with this, there was some evidence that females deviated from reward maximization more than males. However, when controlling for body weight, females had a higher normalized rate of reinforcement than males. Measures of reward maximization were only weakly associated with traditional DD measures and may represent distinctive underlying processes. Taken together, females performance differed from males with regard to reward maximization that were not observed utilizing traditional measures of DD, suggesting that the patch depletion model was more sensitive to modest sex differences when compared to traditional DD measures in a large sample of HS rats.
Inhibition of DYRK1B suppresses inflammation in allergic contact dermatitis model and Th1/Th17 immune response
Authors: Wongchang Thamrong , Pluangnooch Panwadee , Hongeng Suradej , Wongkajornsilp Adisak , Thumkeo Dean , Soontrapa Kitipong
Published: April 2023

Allergic contact dermatitis (ACD) is a type IV hypersensitivity mainly mediated by Th1/Th17 immune response. Topical corticosteroid is currently the first-line treatment for allergic contact dermatitis (ACD) and systemic administration of immunosuppressive drugs are used in patients with severe disseminated cases. However, increased risk of adverse effects has limited their use. Thus, the development of a novel immunosuppressant for ACD with low toxicity is a challenging issue. In this study, we began our study by using a murine contact hypersensitivity (CHS) model of ACD to examine the immunosuppressive effects of DYRK1B inhibition. We found that mice treated with a selective DYRK1B inhibitor show reduced ear inflammation. In addition, a significant reduction of Th1 and Th17 cells in the regional lymph node upon DYRK1B inhibition was observed by FACS analysis. Studies in vitro further revealed that DYRK1B inhibitor does not only suppressed Th1 and Th17 differentiation, but also promotes regulatory T cells (Treg) differentiation. Mechanistically, FOXO1 signaling was enhanced due to the suppression of FOXO1Ser329 phosphorylation in the presence of DYRK1B inhibitor. Therefore, these findings suggest that DYRK1B regulates CD4 T cell differentiation through FOXO1 phosphorylation and DYRK1B inhibitor has a potential as a novel agent for treatment of ACD.
Use of machine learning-based integration to develop an immune-related signature for improving prognosis in patients with gastric cancer
Authors: Ning Jingyuan , Sun Keran , Fan Xiaoqing , Jia Keqi , Meng Lingtong , Wang Xiuli , Li Hui , Ma Ruixiao , Liu Subin , Li Feng , Wang Xiaofeng
Published: April 2023

Gastric cancer is one of the most common malignancies. Although some patients benefit from immunotherapy, the majority of patients have unsatisfactory immunotherapy outcomes, and the clinical significance of immune-related genes in gastric cancer remains unknown. We used the single-sample gene set enrichment analysis (ssGSEA) method to evaluate the immune cell content of gastric cancer patients from TCGA and clustered patients based on immune cell scores. The Weighted Correlation Network Analysis (WGCNA) algorithm was used to identify immune subtype-related genes. The patients in TCGA were randomly divided into test 1 and test 2 in a 1:1 ratio, and a machine learning integration process was used to determine the best prognostic signatures in the total cohort. The signatures were then validated in the test 1 and the test 2 cohort. Based on a literature search, we selected 93 previously published prognostic signatures for gastric cancer and compared them with our prognostic signatures. At the single-cell level, the algorithms "Seurat," "SCEVAN", "scissor", and "Cellchat" were used to demonstrate the cell communication disturbance of high-risk cells. WGCNA and univariate Cox regression analysis identified 52 prognosis-related genes, which were subjected to 98 machine-learning integration processes. A prognostic signature consisting of 24 genes was identified using the StepCox[backward] and Enet[alpha = 0.7] machine learning algorithms. This signature demonstrated the best prognostic performance in the overall, test1 and test2 cohort, and outperformed 93 previously published prognostic signatures. Interaction perturbations in cellular communication of high-risk T cells were identified at the single-cell level, which may promote disease progression in patients with gastric cancer. We developed an immune-related prognostic signature with reliable validity and high accuracy for clinical use for predicting the prognosis of patients with gastric cancer.
Short-term forecasts of streamflow in the UK based on a novel hybrid artificial intelligence algorithm
Authors: Di Nunno Fabio , de Marinis Giovanni , Granata Francesco
Published: April 2023

In recent years, the growing impact of climate change on surface water bodies has made the analysis and forecasting of streamflow rates essential for proper planning and management of water resources. This study proposes a novel ensemble (or hybrid) model, based on the combination of a Deep Learning algorithm, the Nonlinear AutoRegressive network with eXogenous inputs, and two Machine Learning algorithms, Multilayer Perceptron and Random Forest, for the short-term streamflow forecasting, considering precipitation as the only exogenous input and a forecast horizon up to 7 days. A large regional study was performed, considering 18 watercourses throughout the United Kingdom, characterized by different catchment areas and flow regimes. In particular, the predictions obtained with the ensemble Machine Learning-Deep Learning model were compared with the ones achieved with simpler models based on an ensemble of both Machine Learning algorithms and on the only Deep Learning algorithm. The hybrid Machine Learning-Deep Learning model outperformed the simpler models, with values of R2 above 0.9 for several watercourses, with the greatest discrepancies for small basins, where high and non-uniform rainfall throughout the year makes the streamflow rate forecasting a challenging task. Furthermore, the hybrid Machine Learning-Deep Learning model has been shown to be less affected by reductions in performance as the forecasting horizon increases compared to the simpler models, leading to reliable predictions even for 7-day forecasts.
Mzion enables deep and precise identification of peptides in data-dependent acquisition proteomics
Authors: Zhang Qiang
Published: April 2023

Sensitive and reliable identification of proteins and peptides pertains the basis of proteomics. We introduce Mzion, a new database search tool for data-dependent acquisition (DDA) proteomics. Our tool utilizes an intensity tally strategy and achieves generally a higher performance in terms of depth and precision across 20 datasets, ranging from large-scale to single-cell proteomics. Compared to several other search engines, Mzion matches on average 20% more peptide spectra at tryptic enzymatic specificity and 80% more at no enzymatic specificity from six large-scale, global datasets. Mzion also identifies more phosphopeptide spectra that can be explained by fewer proteins, demonstrated by six large-scale, local datasets corresponding to the global data. Our findings highlight the potential of Mzion for improving proteomic analysis and advancing our understanding of protein biology.
Circadian rhythm biomarker from wearable device data is related to concurrent antidepressant treatment response
Authors: Ali Farzana Z. , Parsey Ramin V. , Lin Shan , Schwartz Joseph , DeLorenzo Christine
Published: April 2023

Major depressive disorder (MDD) is associated with circadian rhythm disruption. Yet, no circadian rhythm biomarkers have been clinically validated for assessing antidepressant response. In this study, 40 participants with MDD provided actigraphy data using wearable devices for one week after initiating antidepressant treatment in a randomized, double-blind, placebo-controlled trial. Their depression severity was calculated pretreatment, after one week and eight weeks of treatment. This study assesses the relationship between parametric and nonparametric measures of circadian rhythm and change in depression. Results show significant association between a lower circadian quotient (reflecting less robust rhythmicity) and improvement in depression from baseline following first week of treatment (estimate = 0.11, F = 7.01, P = 0.01). There is insufficient evidence of an association between circadian rhythm measures acquired during the first week of treatment and outcomes after eight weeks of treatment. Despite this lack of association with future treatment outcome, this scalable, cost-effective biomarker may be useful for timely mental health care through remote monitoring of real-time changes in current depression.
Regulation of synaptic connectivity in schizophrenia spectrum by mutual neuron-microglia interaction
Authors: Breitmeyer Ricarda , Vogel Sabrina , Heider Johanna , Hartmann Sophia-Marie , Wüst Richard , Keller Anna-Lena , Binner Anna , Fitzgerald Julia C. , Fallgatter Andreas J. , Volkmer Hansjürgen
Published: April 2023

The examination of post-mortem brain tissue suggests synaptic loss as a central pathological hallmark of schizophrenia spectrum (SCZ), which is potentially related to activated microglia and increased inflammation. Induced pluripotent stem cells serve as a source for neurons and microglia-like cells to address neuron-microglia interactions. Here, we present a co-culture model of neurons and microglia, both of human origin, to show increased susceptibility of neurons to microglia-like cells derived from SCZ patients. Analysis of IBA-1 expression, NFκB signaling, transcription of inflammasome-related genes, and caspase-1 activation shows that enhanced, intrinsic inflammasome activation in patient-derived microglia exacerbates neuronal deficits such as synaptic loss in SCZ. Anti-inflammatory pretreatment of microglia with minocycline specifically rescued aberrant synapse loss in SCZ and reduced microglial activation. These findings open up possibilities for further research in larger cohorts, focused clinical work and longitudinal studies that could facilitate earlier therapeutic intervention.
RNA-DNA interactomes of three prokaryotes uncovered by proximity ligation
Authors: Gavrilov Alexey A. , Evko Grigory S. , Galitsyna Aleksandra A. , Ulianov Sergey V. , Kochetkova Tatiana V. , Merkel Alexander Y. , Tyakht Alexander V. , Razin Sergey V.
Published: April 2023

Proximity ligation approaches, which are widely used to study the spatial organization of the genome, also make it possible to reveal patterns of RNA-DNA interactions. Here, we use RedC, an RNA-DNA proximity ligation approach, to assess the distribution of major RNA types along the genomes of E. coli, B. subtilis, and thermophilic archaeon T. adornatum. We find that (i) messenger RNAs preferentially interact with their cognate genes and the genes located downstream in the same operon, which is consistent with polycistronic transcription; (ii) ribosomal RNAs preferentially interact with active protein-coding genes in both bacteria and archaea, indicating co-transcriptional translation; and (iii) 6S noncoding RNA, a negative regulator of bacterial transcription, is depleted from active genes in E. coli and B. subtilis. We conclude that the RedC data provide a rich resource for studying both transcription dynamics and the function of noncoding RNAs in microbial organisms.
Tetramethylphosphinane as a new secondary phosphine synthon
Authors: Nobbs James D. , Sugiarto Sigit , See Xin Yi , Cheong Choon Boon , Aitipamula Srinivasulu , Stubbs Ludger P. , van Meurs Martin
Published: April 2023

Secondary phosphines are important building blocks in organic chemistry as their reactive P—H bond enables construction of more elaborate molecules. In particular, they can be used to construct tertiary phosphines that have widespread applications as organocatalysts, and as ligands in metal-complex catalysis. We report here a practical synthesis of the bulky secondary phosphine synthon 2,2,6,6-tetramethylphosphinane (TMPhos). Its nitrogen analogue tetramethylpiperidine, known for over a century, is used as a base in organic chemistry. We obtained TMPhos on a multigram scale from an inexpensive air-stable precursor, ammonium hypophosphite. TMPhos is also a close structural relative of di-tert-butylphosphine, a key component of many important catalysts. Herein we also describe the synthesis of key derivatives of TMPhos, with potential applications ranging from CO2 conversion to cross-coupling and beyond. The availability of a new core phosphine building block opens up a diverse array of opportunities in catalysis.
Discovery of diarylpyrimidine derivatives bearing piperazine sulfonyl as potent HIV-1 nonnucleoside reverse transcriptase inhibitors
Authors: Jiang Xiangyi , Huang Boshi , Rumrill Shawn , Pople David , Zalloum Waleed A. , Kang Dongwei , Zhao Fabao , Ji Xiangkai , Gao Zhen , Hu Lide , Wang Zhao , Xie Minghui , De Clercq Erik , Ruiz Francesc X. , Arnold Eddy , Pannecouque Christophe , Liu Xinyong , Zhan Peng
Published: April 2023

HIV-1 reverse transcriptase is one of the most attractive targets for the treatment of AIDS. However, the rapid emergence of drug-resistant strains and unsatisfactory drug-like properties seriously limit the clinical application of HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs). Here we show that a series of piperazine sulfonyl-bearing diarylpyrimidine-based NNRTIs were designed to improve the potency against wild-type and NNRTI-resistant strains by enhancing backbone-binding interactions. Among them, compound 18b1 demonstrates single-digit nanomolar potency against the wild-type and five mutant HIV-1 strains, which is significantly better than the approved drug etravirine. The co-crystal structure analysis and molecular dynamics simulation studies were conducted to explain the broad-spectrum inhibitory activity of 18b1 against reverse transcriptase variants. Besides, compound 18b1 demonstrates improved water solubility, cytochrome P450 liability, and other pharmacokinetic properties compared to the currently approved diarylpyrimidine (DAPY) NNRTIs. Therefore, we consider compound 18b1 a potential lead compound worthy of further study.
Electrocatalysts for value-added electrolysis coupled with hydrogen evolution
Authors: Moges Endalkachew Asefa , Chang Chia-Yu , Tsai Meng-Che , Su Wei-Nien , Hwang Bing Joe
Published: April 2023

Recent progresses of value-added electrolysis that replace OER with value-added anodic reactions. Representation of the elements: hydrogen (white color), carbon (gray), oxygen (red), nitrogen (blue), and iodine (magenta).
Mechanical and electrical properties of a modified carbon nanotube-mediated hydrogel as a strain sensor
Authors: Huang Xinmin , Yan Zhongjie , Yang Lianhe , Meng Lingling
Published: April 2023

Conductive hydrogels with high mechanical toughness, self-recovery ability, and electrical conductivity were prepared by a one-pot method.
A substrate-dependent mechanism for nickel-catalyzed N-allylation with allylic alcohols: nucleophilic attack vs. reductive elimination
Authors: Yao Ruiming , Jing Yaru , Liu Jiahao , Liu Yan , Wang Tiejun , Ke Zhuofeng
Published: April 2023

The mechanism of N-allylation of allylic alcohols via π-allylmetal is substrate-dependent, and is influenced by the combined effect of nucleophilicity and steric hindrance.
Waypoint selection for unmanned aerial vehicle‐aided calibration in wireless positioning networks
Authors: Wu Zhen , Yao Zheng , Lu Mingquan
Published: April 2023

Deploying an unmanned aerial vehicle (UAV) to scatter positioning beacons and further calibrate their positions by obtaining range measurements enables the establishment of a wireless positioning network in GNSS‐denied environments where hand placement is not an option. The influence of the UAV trajectory on the calibration quality is investigated and methods to find optimal waypoints at which the UAV makes observations are determined. A Fisher information matrix‐based metric is devised and two waypoint selection algorithms are proposed to optimise calibration quality, one‐off waypoint selection, and iterative and incremental waypoint selection. Numerical results show that optimised waypoints provide more information about beacon positions and therefore produce a more accurate wireless positioning network.
Brillouin scattering spectroscopy for studying human anatomy: Towardsin situmechanical characterization of soft tissue
Authors: Pruidze Paata , Chayleva Elena , Weninger Wolfgang J. , Elsayad Kareem
Published: April 2023

Brillouin light scattering (BLS) spectroscopy is a label-free method of measuring the GHz-frequency viscoelastic properties. The measured longitudinal modulus is acutely sensitive to the degree of hydration, crosslinking, and temperature, which can be indicative of tissue health. As such, performingin situmeasurements on humans is particularly desirable for exploring potential clinical translation, however, is not possible with existing designs which are coupled to bench-top microscopes. Here we introduce a robust fiber coupled hand-held BLS probe and demonstrate its reliability for measuring excised human tissue. We verify its accuracy using confocal BLS microscopy and further show that it is possible to distinguish veins, arteries, nerves and muscles based on their BLS-measured viscoelasticity. This provides a necessary first step towardsin situclinical BLS viscoelasticity studies of human tissue.