bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Machine Learning Techniques to Predict the Likelihood of Mental Health Conditions Following a First mTBI
Authors: Dabek Filip , Hoover Peter , Jorgensen-Wagers Kendra , Wu Tim , Caban Jesus J.
Published: February 2022

Objective

Limited research has evaluated the utility of machine learning models and longitudinal data from electronic health records (EHR) to forecast mental health outcomes following a traumatic brain injury (TBI). The objective of this study is to assess various data science and machine learning techniques and determine their efficacy in forecasting mental health (MH) conditions among active duty Service Members (SMs) following a first diagnosis of mild traumatic brain injury (mTBI).

Materials and Methods

Patient demographics and encounter metadata of 35,451 active duty SMs who have sustained an initial mTBI, as documented within the EHR, were obtained. All encounter records from a year prior and post index mTBI date were collected. Patient demographics, ICD-9-CM and ICD-10 codes, enhanced diagnostic related groups, and other risk factors estimated from the year prior to index mTBI were utilized to develop a feature vector representative of each patient. To embed temporal information into the feature vector, various window configurations were devised. Finally, the presence or absence of mental health conditions post mTBI index date were used as the outcomes variable for the models.

Results

When evaluating the machine learning models, neural network techniques showed the best overall performance in identifying patients with new or persistent mental health conditions post mTBI. Various window configurations were tested and results show that dividing the observation window into three distinct date windows [−365:−30, −30:0, 0:14] provided the best performance. Overall, the models described in this paper identified the likelihood of developing MH conditions at [14:90] days post-mTBI with an accuracy of 88.2%, an AUC of 0.82, and AUC-PR of 0.66.

Discussion

Through the development and evaluation of different machine learning models we have validated the feasibility of designing algorithms to forecast the likelihood of developing mental health conditions after the first mTBI. Patient attributes including demographics, symptomatology, and other known risk factors proved to be effective features to employ when training ML models for mTBI patients. When patient attributes and features are estimated at different time window, the overall performance increase illustrating the importance of embedding temporal information into the models. The addition of temporal information not only improved model performance, but also increased interpretability and clinical utility.

Conclusion

Predictive analytics can be a valuable tool for understanding the effects of mTBI, particularly when identifying those individuals at risk of negative outcomes. The translation of these models from retrospective study into real-world validation models is imperative in the mitigation of negative outcomes with appropriate and timely interventions.
Boosting Recovery During Sleep by Means of Auditory Stimulation
Authors: Krugliakova Elena , Skorucak Jelena , Sousouri Georgia , Leach Sven , Snipes Sophia , Ferster Maria Laura , Da Poian Giulia , Karlen Walter , Huber Reto
Published: February 2022

Sufficient recovery during sleep is the basis of physical and psychological well-being. Understanding the physiological mechanisms underlying this restorative function is essential for developing novel approaches to promote recovery during sleep. Phase-targeted auditory stimulation (PTAS) is an increasingly popular technique for boosting the key electrophysiological marker of recovery during sleep, slow-wave activity (SWA, 1–4 Hz EEG power). However, it is unknown whether PTAS induces physiological sleep. In this study, we demonstrate that, when applied during deep sleep, PTAS accelerates SWA decline across the night which is associated with an overnight improvement in attentional performance. Thus, we provide evidence that PTAS enhances physiological sleep and demonstrate under which conditions this occurs most efficiently. These findings will be important for future translation into clinical populations suffering from insufficient recovery during sleep.
Therapeutic Interventions of Gut-Brain Axis as Novel Strategies for Treatment of Alcohol Use Disorder Associated Cognitive and Mood Dysfunction
Authors: Li Xin , Chen Le-Mei , Kumar Gajendra , Zhang Shan-Jin , Zhong Quan-hai , Zhang Hong-Yan , Gui Guan , Wu Lv-Le , Fan Hui-Zhen , Sheng Jian-Wen
Published: February 2022

Alcohol use disorders (AUD) is characterized by persistent or intermittent alcohol cravings and compulsive drinking. The functional changes in the central nervous system (CNS) after alcohol consumption are alcohol-associated cognitive impairment and mood disorders, which are major health issues reported in AUDs. Studies have shown that transferring the intestinal microbiota from AUDs patients to germ-free animals causes learning and memory dysfunction, depression and anxiety-like behavior, indicating the vital role of intestinal microbiota in development of neuropsychiatric disorders in AUD. Intestinal flora composition of AUD patients are significantly different from normal people, suggesting that intestinal flora imbalance orchestrate the development of neuropsychiatric disorders in AUD. Studies suggests that gut microbiome links bidirectional signaling network of the enteric nervous system (ENS) to central nervous system (CNS), forming gut-microbe-brain axis (brain-gut axis). In this review, we discussed pathogenesis and possible treatment of AUD-induced cognitive deficits, anxiety, and depression disorders. Further, we described the mechanism of intestinal flora imbalance and dysfunction of hippocampus-amygdala-frontal cortex (gut-limbic circuit system dysfunction). Therefore, we postulate therapeutic interventions of gut-brain axis as novel strategies for treatment of AUD-induced neuropsychiatric disorders.
Metabotropic Glutamate Receptor 5 Antagonism Reduces Pathology and Differentially Improves Symptoms in Male and Female Heterozygous zQ175 Huntington’s Mice
Authors: Li Si Han , Colson Tash-Lynn L. , Abd-Elrahman Khaled S. , Ferguson Stephen S. G.
Published: February 2022

Huntington’s disease (HD) is an inherited autosomal dominant neurodegenerative disorder that leads to progressive motor and cognitive impairment. There are currently no available disease modifying treatments for HD patients. We have previously shown that pharmacological blockade of metabotropic glutamate receptor 5 (mGluR5) signaling rescues motor deficits, improves cognitive impairments and mitigates HD neuropathology in male zQ175 HD mice. Mounting evidence indicates that sex may influence HD progression and we have recently reported a sex-specific pathological mGluR5 signaling in Alzheimer’s disease (AD) mice. Here, we compared the outcomes of treatment with the mGluR5 negative allosteric modulator CTEP (2-chloro-4-[2-[2,5-dimethyl-1-[4-(trifluoromethoxy)phenyl]imidazol-4-yl]ethynyl]pyridine) in both male and female symptomatic zQ175 mice. We found that female zQ175 mice required a longer treatment duration with CTEP than male mice to show improvement in their rotarod performance. Unlike males, chronic CTEP treatment did not improve the grip strength nor reverse the cognitive decline of female zQ175 mice. However, CTEP reduced the number of huntingtin aggregates, improved neuronal survival and decreased microglia activation in the striatum of both male and female zQ175 mice. Together, our results indicate that mGluR5 antagonism can reduce HD neuropathology in both male and female zQ175 HD mice, but sex has a clear impact on the efficacy of the treatment and must be taken into consideration for future HD drug development.
Time to Recover From Daily Caffeine Intake
Authors: Lin Yu-Shiuan , Weibel Janine , Landolt Hans-Peter , Santini Francesco , Garbazza Corrado , Kistler Joshua , Rehm Sophia , Rentsch Katharina , Borgwardt Stefan , Cajochen Christian , Reichert Carolin F.
Published: February 2022

Caffeine elicits widespread effects in the central nervous system and is the most frequently consumed psychostimulant worldwide. First evidence indicates that, during daily intake, the elimination of caffeine may slow down, and the primary metabolite, paraxanthine, may accumulate. The neural impact of such adaptions is virtually unexplored. In this report, we leveraged the data of a laboratory study with N = 20 participants and three within-subject conditions: caffeine (150 mg caffeine × 3/day × 10 days), placebo (150 mg mannitol × 3/day × 10 days), and acute caffeine deprivation (caffeine × 9 days, afterward placebo × 1 day). On day 10, we determined the course of salivary caffeine and paraxanthine using liquid chromatography-mass spectrometry coupled with tandem mass spectrometry. We assessed gray matter (GM) intensity and cerebral blood flow (CBF) after acute caffeine deprivation as compared to changes in the caffeine condition from our previous report. The results indicated that levels of paraxanthine and caffeine remained high and were carried overnight during daily intake, and that the levels of paraxanthine remained elevated after 24 h of caffeine deprivation compared to placebo. After 36 h of caffeine deprivation, the previously reported caffeine-induced GM reduction was partially mitigated, while CBF was elevated compared to placebo. Our findings unveil that conventional daily caffeine intake does not provide sufficient time to clear up psychoactive compounds and restore cerebral responses, even after 36 h of abstinence. They also suggest investigating the consequences of a paraxanthine accumulation during daily caffeine intake.
Modeling the Contribution of Meat to Global Nutrient Availability
Authors: Smith Nick W. , Fletcher Andrew J. , Hill Jeremy P. , McNabb Warren C.
Published: February 2022

An increasing global population requires increasing food and nutrient availability. Meat is recognized as a nutrient dense food, particularly notable for its high-quality protein content, B vitamin and mineral content. However, it is not known how important meat is currently in nourishing the global population. The DELTA Model was used to calculate the contribution of meat (defined as animal flesh, excluding fish and seafood) to the global availability of 29 nutrients. This model utilizes global food production and use data, coupled with data for food waste, food nutrient composition and nutrient bioavailability to calculate the total amount of each nutrient available for consumption by the global population. Around 333 million tons of meat were produced globally in 2018, 95% of which was available as food, constituting ~7% of total food mass. Meat's contribution to nutrient availability was disproportionately higher than this: meat provided 11% of global food energy availability, 29% of dietary fat and 21% of protein. For the micronutrients, meat provided high proportions of vitamins: A (24%), B1 and B2 (15% each), B5 (10%), B6 (13%), and B12 (56%). Meat also provided high proportions of several trace elements: zinc (19%), selenium (18%), iron (13%), phosphorous (11%), and copper (10%). Meat is a poor contributor to fiber, magnesium and vitamins C and E. Meat was responsible for 16% (cystine) to 32% (lysine) of global availability of the bioavailable indispensable amino acids included in the model, due partly to the high digestibility of these nutrients from meat (83–100%). Of the total meat mass available as food in 2018, 23% was ruminant meat, 34% poultry meat, 32% pig meat, 2% other meat, and 9% offal and fats. The disproportionate contribution of meat to the global availability of nutrients emphasizes its important place in delivering nutrition to the current global population.
Color Shade Nets Affect Plant Growth and Seasonal Leaf Quality of Camellia sinensis Grown in Mississippi, the United States
Authors: Zhang Qianwen , Bi Guihong , Li Tongyin , Wang Qiushuang , Xing Zhiheng , LeCompte Judson , Harkess Richard L.
Published: February 2022

Shading modifies the microenvironment and can provide plants with some protection from frequent heat, drought, frost, and hail induced by climate change and has the potential to improve plant growth, yield, and quality. Tea (Camellia sinensis) is an ancient plant originating from tropical and subtropical regions and prefers to grow in partial shade under the forest canopy. The emerging tea industry in the United States (US) requires research support on establishing tea fields in novel environmental conditions as well as on producing high-quality tea products. This study investigated the effects of black, blue, and red shade nets on tea plant growth and seasonal leaf qualities in the southeastern US with a humid subtropical climate. When compared to no-shade control, black, blue, and red shade nets increased plant growth index (PGI), net photosynthetic rate (Pn), and stomatal conductance (gs), decreased air and leaf surface temperatures in summer, and reduced cold damage in winter. No significant difference was found among the black, blue, and red shade nets on tea plant growth. Varying contents of total polyphenols, carbohydrates, free amino acids, L-theanine, gallic acid, caffeine, and catechins in fresh tea leaves were observed among different shade treatments and harvesting seasons. 69.58% of the variations were depicted in a biplot by principal component analysis. Red shade was considered helpful for improving green tea quality by increasing the content of L-theanine and free amino acids in tea leaves collected in spring and fall when compared to no-shade control.
Egg-Phosphatidylcholine Attenuates T-Cell Dysfunction in High-Fat Diet Fed Male Wistar Rats
Authors: Azarcoya-Barrera Jessy , Wollin Bethany , Veida-Silva Hellen , Makarowski Alexander , Goruk Susan , Field Catherine J. , Jacobs René L. , Richard Caroline
Published: February 2022

Obesity is associated with immune dysfunction including an impaired T-cell function characterized by a lower IL-2 (proliferation marker) production after stimulation. Phosphatidylcholine (PC), a form of choline mostly found in eggs, has been shown to beneficially modulate T-cell responses during the lactation period by increasing the production of IL-2. To determine the impact of egg-PC as part of a high-fat diet on immune function we randomly fed male Wistar rats one of three diets containing the same amount of total choline but differing in the form of choline: 1—Control low fat [CLF, 10% wt/wt fat, 100% free choline (FC)]; 2— Control high-fat (CHF, 25% wt/wt fat, 100% FC); 3— PC high-fat (PCHF, 25% wt/wt, 100% PC). After 9 weeks of feeding, rats were euthanized. Cell phenotypes and ex vivo cytokine production by splenocytes stimulated with phorbol 12-myristate 13-acetate plus ionomycin (PMA+I), lipopolysaccharide (LPS) and pokeweed (PWM) were measured by flow cytometry and ELISA, respectively. Rats fed the PCHF diet had a lower proportion of CD3+ cells when compared to both the CLF and the CHF. Following PMA+I stimulation, splenocytes from the CHF group produced less IL-2 and TNF-α compared to CLF and PCHF groups. No significant differences in cytokine production were found among groups after LPS and PWM stimulation. Our results show that feeding a high-fat diet impairs T-cell responses, as measured by ex vivo cytokine production, which can be attenuated by providing egg-PC.
Relationship Between Nutritional Status and Clinical Outcome in Patients With Gastrointestinal Stromal Tumor After Surgical Resection
Authors: Ding Ping'an , Guo Honghai , Sun Chenyu , Yang Peigang , Tian Yuan , Liu Yang , Zhang Zhidong , Wang Dong , Zhao Xuefeng , Tan Bibo , Liu Yu , Li Yong , Zhao Qun
Published: February 2022

Background

Currently, gastrointestinal stromal tumors (GIST) are the most common mesenchymal tumors in the gastrointestinal tract, and surgical resection is the main treatment. Malnutrition after gastrointestinal surgery is not uncommon, which may have adverse effects on postoperative recovery and prognosis. However, the nutritional status of GIST patients after surgical resection and its impact on clinical outcomes have received less attention. Therefore, the aim of this study was to dynamically evaluate the nutritional status of GIST patients undergoing surgical resection, and to analyze the correlation between nutritional status and clinical outcomes.

Methods

We retrospectively analyzed the clinical data of GIST patients who underwent surgical resection in the Fourth Hospital of Hebei Medical University from January 2016 to January 2020. Nutritional risk screening 2002 (NRS2002) and Patient-Generated Subjective Global Assessment (PG-SGA) were used to assess the nutritional status of all patients at admission and discharge, and the correlation between nutritional risk and clinical outcomes was analyzed.

Results

A total of 413 GIST patients were included in this study, among which 114 patients had malnutrition risk at admission (NRS2002 score ≥ 3), and 65 patients had malnutrition (PG-SGA score ≥ 4). The malnutrition risk rate (27.60 vs. 46.73%, p < 0.001) and malnutrition incidence (15.73 vs. 37.29%, p < 0.001) at admission were lower than those at discharge. Compared with the laboratory results at admission, the albumin, prealbumin, and total protein of the patients at discharge were significantly lower (all p < 0.05). And there was a negative correlation between PG-SGA and clinical outcome (all p < 0.05).

Conclusion

The nutritional status of GIST patients after surgical resection at discharge was worse than that at admission, and malnutrition is an important risk factor leading to poor clinical outcomes.
Concurrent Chemoradiotherapy With Nedaplatin Versus Cisplatin in Patients With Stage IIB-IVA Cervical Cancer: A Randomized Phase III Trial
Authors: He Shasha , Wang Yan , Lai Yulin , Cao Xinping , Ren Yufeng , Chen Yong
Published: February 2022

Background

In this trial, we aimed to assess the efficacy and safety of radiotherapy with nedaplatin or cisplatin in patients with locally advanced cervical cancer.

Methods

We conducted an open-label, non-inferiority, phase III, randomized, controlled trial. Eligible patients with stage IIB-IVA cervical carcinoma were randomly assigned to receive either nedaplatin or cisplatin for two cycles concurrently with radiotherapy. We reported the therapy-associated harms and survival. The study was registered with chictr.org.cn, number ChiCTR1800020527.

Results

We randomly assigned 68 patients to nedaplatin-based or cisplatin-based concurrent chemoradiotherapy. Study treatment was stopped early after a data analysis found a higher number of patients suffered severe hematologic harms in the nedaplatin group than in the cisplatin group. Patients in the nedaplatin group had a significantly higher frequency of grade 3-4 neutropenia (19·4% vs. 13%; P < 0·001), severe thrombocytopenia (16·1% vs. 4·3%), and grade 1-2 anemia (51·6% vs. 43·5%) than patients in the cisplatin group. The 1-year PFS and OS in the nedaplatin and cisplatin groups were similar.

Conclusion

Our findings showed that nedaplatin-based concurrent chemoradiotherapy expressed remarkably higher severe hematologic harms which were mortal. Though the results were negative, the experiences and lessons we learned from it were important.
WEENet: An Intelligent System for Diagnosing COVID-19 and Lung Cancer in IoMT Environments
Authors: Muhammad Khan , Ullah Hayat , Khan Zulfiqar Ahmad , Saudagar Abdul Khader Jilani , AlTameem Abdullah , AlKhathami Mohammed , Khan Muhammad Badruddin , Abul Hasanat Mozaherul Hoque , Mahmood Malik Khalid , Hijji Mohammad , Sajjad Muhammad
Published: February 2022

The coronavirus disease 2019 (COVID-19) pandemic has caused a major outbreak around the world with severe impact on health, human lives, and economy globally. One of the crucial steps in fighting COVID-19 is the ability to detect infected patients at early stages and put them under special care. Detecting COVID-19 from radiography images using computational medical imaging method is one of the fastest ways to diagnose the patients. However, early detection with significant results is a major challenge, given the limited available medical imaging data and conflicting performance metrics. Therefore, this work aims to develop a novel deep learning-based computationally efficient medical imaging framework for effective modeling and early diagnosis of COVID-19 from chest x-ray and computed tomography images. The proposed work presents “WEENet” by exploiting efficient convolutional neural network to extract high-level features, followed by classification mechanisms for COVID-19 diagnosis in medical image data. The performance of our method is evaluated on three benchmark medical chest x-ray and computed tomography image datasets using eight evaluation metrics including a novel strategy of cross-corpse evaluation as well as robustness evaluation, and the results are surpassing state-of-the-art methods. The outcome of this work can assist the epidemiologists and healthcare authorities in analyzing the infected medical chest x-ray and computed tomography images, management of the COVID-19 pandemic, bridging the early diagnosis, and treatment gap for Internet of Medical Things environments.
Development and Validation of Subjective Financial Distress Questionnaire (SFDQ): A Patient Reported Outcome Measure for Assessment of Financial Toxicity Among Radiation Oncology Patients
Authors: Dar Mukhtar Ahmad , Chauhan Richa , Murti Krishna , Trivedi Vinita , Dhingra Sameer
Published: February 2022

Background

Financial toxicity is a consequence of subjective financial distress experienced by cancer patients as a result of treatment expenditures. Financial toxicity has been associated with poor quality of life, early mortality, and non-adherence. It is evident from the literature that the currently available instruments for the assessment of financial toxicity do not measure coping and support seeking domains. The aim of this study was to develop an instrument for the assessment of financial toxicity among radiation oncology patients that captures and integrates all the relevant domains of subjective financial distress.

Materials and Methods

The study was conducted among Head & Neck cancer (HNC) patients (age ≥18 years) who have completed the radiotherapy either as stand-alone or part of a multimodal treatment. Literature review, expert opinion, and patient interviews were used for scale item generation. The validity and underlying factor structure were evaluated by Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). The reliability and internal consistency of the final scale was assessed using Cronbach’s alpha coefficient.

Results

A total of 17 items were identified for scale development. The preliminary 17-item instrument was administered to 142 HNC patients. Among 142 participants, 85.9% were male and 98.6% were from rural areas. EFA was performed on 17 items and three items were removed (factor loadings <0.5). The remaining 14 items loaded onto three factors (eigenvalue >1) explaining 62.0% of the total variance. The Chi-square goodness of fit test in CFA and the values of other model fit indices, namely, RMSEA = 0.045, SRMR = 0.014, GFI = 0.92, CFI = 0.98, and TLI=0.97 indicate a good model fit suggesting the three-factor model adequately fits the data. The Cronbach’s α for the final 14-item scale was 0.87 indicating excellent reliability and the Cronbach’s α coefficient of all the individual 14 items was ≥0.85 (range 0.85–0.88).

Conclusion

The SFDQ showed excellent validity and reliability. SFDQ captures and integrates all the relevant domains of financial toxicity. However, the provisional SFDQ instrument warrants further larger sample studies for validation and psychometric evaluation in different primary cancer subsites and treatment modalities from multiple cancer centers to improve the generalizability of this instrument.
Three-Dimensional Convolutional Neural Network-Based Prediction of Epidermal Growth Factor Receptor Expression Status in Patients With Non-Small Cell Lung Cancer
Authors: Huang Xuemei , Sun Yingli , Tan Mingyu , Ma Weiling , Gao Pan , Qi Lin , Lu Jinjuan , Yang Yuling , Wang Kun , Chen Wufei , Jin Liang , Kuang Kaiming , Duan Shaofeng , Li Ming
Published: February 2022

Objectives

EGFR testing is a mandatory step before targeted therapy for non-small cell lung cancer patients. Combining some quantifiable features to establish a predictive model of EGFR expression status, break the limitations of tissue biopsy.

Materials and Methods

We retrospectively analyzed 1074 patients of non-small cell lung cancer with complete reports of EGFR gene testing. Then manually segmented VOI, captured the clinicopathological features, analyzed traditional radiology features, and extracted radiomic, and deep learning features. The cases were randomly divided into training and test set. We carried out feature screening; then applied the light GBM algorithm, Resnet-101 algorithm, logistic regression to develop sole models, and fused models to predict EGFR mutation conditions. The efficiency of models was evaluated by ROC and PRC curves.

Results

We successfully established Modelclinical, Modelradiomic, ModelCNN (based on clinical-radiology, radiomic and deep learning features respectively), Modelradiomic+clinical (combining clinical-radiology and radiomic features), and ModelCNN+radiomic+clinical (combining clinical-radiology, radiomic, and deep learning features). Among the prediction models, ModelCNN+radiomic+clinical showed the highest performance, followed by ModelCNN, and then Modelradiomic+clinical. All three models were able to accurately predict EGFR mutation with AUC values of 0.751, 0.738, and 0.684, respectively. There was no significant difference in the AUC values between ModelCNN+radiomic+clinical and ModelCNN. Further analysis showed that ModelCNN+radiomic+clinical effectively improved the efficacy of Modelradiomic+clinical and showed better efficacy than ModelCNN. The inclusion of clinical-radiology features did not effectively improve the efficacy of Modelradiomic.

Conclusions

Either deep learning or radiomic signature-based models can provide a fairly accurate non-invasive prediction of EGFR expression status. The model combined both features effectively enhanced the performance of radiomic models and provided marginal enhancement to deep learning models. Collectively, fusion models offer a novel and more reliable way of providing the efficacy of currently developed prediction models, and have far-reaching potential for the optimization of noninvasive EGFR mutation status prediction methods.
Effects of Metformin Combined With Antifolates on HepG2 Cell Metabolism and Cellular Proliferation
Authors: Tawfik Sherouk M. , Abdollah Maha R. A. , Elmazar Mohey M. , El-Fawal Hassan A. N. , Abdelnaser Anwar
Published: February 2022

Hepatocellular carcinoma (HCC), one of the most prevalent types of cancers worldwide, continues to maintain high levels of resistance to standard therapy. As clinical data revealed poor response rates, the need for developing new methods has increased to improve the overall wellbeing of patients with HCC. Furthermore, a growing body of evidence shows that cancer metabolic changes are a key feature of many types of human malignancies. Metabolic reprogramming refers to cancer cells’ ability to change their metabolism in order to meet the increased energy demand caused by continuous growth, rapid proliferation, and other neoplastic cell characteristics. For these reasons, metabolic pathways may become new therapeutic and chemopreventive targets. The aim of this study was to investigate the metabolic alterations associated with metformin (MET), an anti-diabetic agent when combined with two antifolate drugs: trimethoprim (TMP) or methotrexate (MTX), and how metabolic changes within the cancer cell may be used to increase cellular death. In this study, single drugs and combinations were investigated using in vitro assays including cytotoxicity assay (MTT), RT-qPCR, annexin V/PI apoptosis assay, scratch wound assay and Seahorse XF analysis, on a human HCC cell line, HepG2. The cytotoxicity assay showed that the IC50 of MET as single therapy was 44.08 mM that was reduced to 22.73 mM and 29.29 mM when combined with TMP and MTX, respectively. The co-treatment of both drugs increased p53 and Bax apoptotic markers, while decreased the anti-apoptotic marker; Bcl-2. Both combinations increased the percentage of apoptotic cells and halted cancer cell migration when compared to MET alone. Furthermore, both combinations decreased the MET-induced increase in glycolysis, while also inducing mitochondrial damage, altering cancer cell bioenergetics. These findings provide an exciting insight into the anti-proliferative and apoptotic effects of MET and anti-folates on HepG2 cells, and how in combination, may potentially combat the aggressiveness of HCC.
Association of Maternal Dietary Habits and MTHFD1 Gene Polymorphisms With Ventricular Septal Defects in Offspring: A Case-Control Study
Authors: Song Xinli , Liu Yiping , Wang Tingting , Zhang Senmao , Sun Mengting , Shu Jing , Wei Jianhui , Diao Jingyi , Li Jinqi , Li Yihuan , Chen Letao , Zhu Ping , Qin Jiabi
Published: February 2022

Objectives

This study aimed at assessing the association between maternal methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) gene polymorphisms, maternal dietary habits, and their interactions with the risk of ventricular septal defects (VSD) in offspring.

Methods

From November 2017 to March 2019, a case-control study comprising 360 mothers of VSD cases and 504 mothers of healthy infants was conducted in Han Chinese populations. The main exposures of interest were maternal dietary habits in early pregnancy and MTHFD1 gene polymorphisms. Logistic regression models were used to estimate the main effects and interaction effects.

Results

It was observed that maternal excessive intake of pickled vegetables (aOR = 1.85, 95%CI: 1.45–2.37), smoked foods (aOR = 1.93, 95%CI: 1.48–2.51), barbecued foods (aOR = 1.74, 95%CI: 1.28–2.36), and fried foods (aOR = 1.68, 95%CI: 1.30–2.17) were associated with a higher risk of VSD in offspring, whereas maternal excessive intake of fresh meat (aOR = 0.61, 95%CI: 0.47–0.79), fish and shrimp (aOR = 0.29, 95%CI: 0.23–0.38), fresh eggs (aOR = 0.54, 95%CI: 0.42–0.70), fresh fruits or vegetables (aOR = 0.44, 95%CI: 0.33–0.60), soy foods (aOR = 0.65, 95%CI: 0.53–0.80), and milk products (aOR = 0.49, 95%CI: 0.40–0.59) could contribute significantly to a lower risk of VSD in offspring. Furthermore, the genetic polymorphisms of maternal MTHFD1 gene at rs1950902 (GA vs. GG: aOR = 0.67, 95%CI: 0.50–0.90) and rs2236222 (GG vs. AA: aOR = 2.75, 95%CI: 1.57–4.83) were significantly associated with the risk of VSD in offspring. In addition, there was a significant interaction effect between maternal dietary habits and MTHFD1 gene polymorphisms on the risk of VSD.

Conclusions

Maternal dietary factors, MTHFD1 genetic polymorphisms, and their interactions were all associated with the risk of VSD in offspring. However, further research in diverse ethnic populations and with a larger sample size is warranted to corroborate our findings.

Trial Registration

Registered in Chinese Clinical Trial Registry Center; registration number, ChiCTR1800016635; registration date, 06/14/2018 (Retrospectively registered); URL of trial registry record, https://www.chictr.org.cn/showproj.aspx?proj=28300.
Caffeine Functions by Inhibiting Dorsal and Ventral Hippocampal Adenosine 2A Receptors to Modulate Memory and Anxiety, Respectively
Authors: Xu Yawei , Ning Yalei , Zhao Yan , Peng Yan , Luo Fen , Zhou Yuanguo , Li Ping
Published: February 2022

As a nonspecific antagonist of the adenosine A2A receptor (A2AR), caffeine enhances learning and improves memory impairment. Simultaneously, the consumption of caffeine correlates with a feeling of anxiety. The hippocampus is functionally differentiated along its dorsal/ventral axis and plays a crucial role both in memory and anxiety. Whether caffeine exerts its regulation by inhibiting A2ARs in different subregions of the hippocampus is still unknown. In the present study, we found that after chronic intake of drinking water containing caffeine (1 g/L, 3 weeks), mice exhibited aggravated anxiety-like behavior and enhanced memory function. Tissue-specific, functional disruption of dorsal hippocampal A2ARs by the CRE-LoxP system prevented the memory-enhancing effect of caffeine, while selective disruption of ventral hippocampal A2ARs blocked the impact of caffeine on anxiety. These results, together with the enhanced memory of dorsal hippocampus A2AR knockout mice and greater anxiety-like behavior of ventral hippocampus A2AR knockout mice without caffeine, indicates a dissociation between the roles of ventral and dorsal hippocampal A2A receptors in caffeine’s effects on anxiety-like and memory-related behavioral measures, respectively. Furthermore, optogenetic activation of dorsal or ventral hippocampal A2ARs reversed the behavioral alterations caused by drinking caffeine, leading to impaired memory or decreased anxiety-like behaviors, respectively. Taken together, our findings suggest that the memory- and anxiety-enhancing effects of caffeine are related to the differential effects of inhibiting A2ARs in the dorsal and ventral hippocampus, respectively.
Transcription Factors Involved in the Development and Prognosis of Cardiac Remodeling
Authors: Hong Jia-Hui , Zhang Hai-Gang
Published: February 2022

To compensate increasing workload, heart must work harder with structural changes, indicated by increasing size and changing shape, causing cardiac remodeling. However, pathological and unlimited compensated cardiac remodeling will ultimately lead to decompensation and heart failure. In the past decade, numerous studies have explored many signaling pathways involved in cardiac remodeling, but the complete mechanism of cardiac remodeling is still unrecognized, which hinders effective treatment and drug development. As gene transcriptional regulators, transcription factors control multiple cellular activities and play a critical role in cardiac remodeling. This review summarizes the regulation of fetal gene reprogramming, energy metabolism, apoptosis, autophagy in cardiomyocytes and myofibroblast activation of cardiac fibroblasts by transcription factors, with an emphasis on their potential roles in the development and prognosis of cardiac remodeling.
From Single to Collective Motion of Social Amoebae: A Computational Study of Interacting Cells
Authors: Moreno Eduardo , Großmann Robert , Beta Carsten , Alonso Sergio
Published: February 2022

The coupling of the internal mechanisms of cell polarization to cell shape deformations and subsequent cell crawling poses many interdisciplinary scientific challenges. Several mathematical approaches have been proposed to model the coupling of both processes, where one of the most successful methods relies on a phase field that encodes the morphology of the cell, together with the integration of partial differential equations that account for the polarization mechanism inside the cell domain as defined by the phase field. This approach has been previously employed to model the motion of single cells of the social amoeba Dictyostelium discoideum, a widely used model organism to study actin-driven motility and chemotaxis of eukaryotic cells. Besides single cell motility, Dictyostelium discoideum is also well-known for its collective behavior. Here, we extend the previously introduced model for single cell motility to describe the collective motion of large populations of interacting amoebae by including repulsive interactions between the cells. We performed numerical simulations of this model, first characterizing the motion of single cells in terms of their polarity and velocity vectors. We then systematically studied the collisions between two cells that provided the basic interaction scenarios also observed in larger ensembles of interacting amoebae. Finally, the relevance of the cell density was analyzed, revealing a systematic decrease of the motility with density, associated with the formation of transient cell clusters that emerge in this system even though our model does not include any attractive interactions between cells. This model is a prototypical active matter system for the investigation of the emergent collective dynamics of deformable, self-driven cells with a highly complex, nonlinear coupling of cell shape deformations, self-propulsion and repulsive cell-cell interactions. Understanding these self-organization processes of cells like their autonomous aggregation is of high relevance as collective amoeboid motility is part of wound healing, embryonic morphogenesis or pathological processes like the spreading of metastatic cancer cells.
Low Valence Nickelates: Launching the Nickel Age of Superconductivity
Authors: Botana Antia S. , Lee Kwan-Woo , Norman Michael R. , Pardo Victor , Pickett Warren E.
Published: February 2022

The discovery of superconductivity in thin films (∼10 nm) of infinite-layer hole-doped NdNiO2 has invigorated the field of high temperature superconductivity research, reviving the debate over contrasting views that nickelates that are isostructural with cuprates are either 1) sisters of the high temperature superconductors, or 2) that differences between nickel and copper at equal band filling should be the focus of attention. Each viewpoint has its merits, and each has its limitations, suggesting that such a simple picture must be superseded by a more holistic comparison of the two classes. Several recent studies have begun this generalization, raising a number of questions without suggesting any consensus. In this paper, we organize the findings of the electronic structures of n-layered NiO2 materials (n = 1 to ∞) to outline (ir)regularities and to make comparisons with cuprates, with the hope that important directions of future research will emerge.
Dynamical Mean Field Studies of Infinite Layer Nickelates: Physics Results and Methodological Implications
Authors: Chen Hanghui , Hampel Alexander , Karp Jonathan , Lechermann Frank , Millis Andrew J.
Published: February 2022

This article summarizes recent work on the many-body (beyond density functional theory) electronic structure of layered rare-earth nickelates, both in the context of the materials themselves and in comparison to the high-temperature superconducting (high-Tc) layered copper-oxide compounds. It aims to outline the current state of our understanding of layered nickelates and to show how the analysis of these fascinating materials can shed light on fundamental questions in modern electronic structure theory. A prime focus is determining how the interacting physics defined over a wide energy range can be estimated and “downfolded” into a low energy theory that would describe the relevant degrees of freedom on the ∼0.5  eV scale and that could be solved to determine superconducting and spin and charge density wave phase boundaries, temperature dependent resistivities, and dynamical susceptibilities.
Nitrogen Supply Affects Yield and Grain Filling of Maize by Regulating Starch Metabolizing Enzyme Activities and Endogenous Hormone Contents
Authors: Yue Kai , Li Lingling , Xie Junhong , Liu Yaoquan , Xie Jianhui , Anwar Sumera , Fudjoe Setor Kwami
Published: February 2022

This study aimed to examine the effect of nitrogen (N) application rate and time on yield, grain filling, starch metabolizing enzymes, and hormones of maize based on a long-term field experiment initiated in 2012. The total N fertilizer dose [(0 (N0), 100 (N1), 200 (N2), and 300 (N3) kg N ha–1] was split into two (T1, one-third at sowing and two-thirds at the six-leaf stage) or three (T2, one-third each at sowing, six-leaf, and eleven-leaf stage) times application. The results showed that the highest yield was obtained under N3T2, N2T1, and N3T2 in 2018, 2019, and 2020, which was 222.49, 185.31, and 194.00% than that of N0 in each year, respectively. N2 and N3 significantly increased the yield through enhancing ears ha–1, grains per plant, and 100-grain weight; however, N2 and N3 did not show a significant difference in yield and above-yield components. In addition, N application time did not significantly change yield under the same N rate. N0 limited the activities of starch metabolizing enzymes, resulting in insufficient accumulation of sucrose and starch. The contents of indole-3-acetic acid, cytokinin, abscisic acid, and gibberellin were decreased under N0 during grain filling. The average grain-filling rate and maximum grain-filling rate (Gmax) and grain weight increment achieving Gmax increased under N2 and N3, and the grain-filling parameters were positively correlated with 100-grain weight. In conclusion, 200 kg N ha–1 with one-third application at sowing and two-thirds application at the six-leaf stage is a suitable N supply way to improve starch metabolizing enzymes, regulate hormone content, and enhance grain-filling rates, and thus increasing the maize yield in the semiarid Loess Plateau of China.
Genetic Diversity and Genome Size Variability in the Russian Genebank Collection of Tea Plant [Camellia sinensis (L). O. Kuntze]
Authors: Samarina Lidiia S. , Matskiv Alexandra O. , Shkhalakhova Ruset M. , Koninskaya Natalia G. , Hanke Magda-Viola , Flachowsky Henryk , Shumeev Alexander N. , Manakhova Karina A. , Malyukova Lyudmila S. , Liu Shengrui , Zhu Juanyan , Gvasaliya Maya V. , Malyarovskaya Valentina I. , Ryndin Alexey V. , Pchikhachev Eduard K. , Reim Stefanie
Published: February 2022

The tea collection of the FRC SSC RAS (Sochi, Maykop in Russia) represents one of the northernmost germplasm comprising a number of locally derived cultivars and ɣ-irradiation mutants. The latter are often characterized by larger genome size, which may lead to better adaptation to biotic and abiotic stress. Such genotypes may be a valuable genetic resource for better adaptability to extreme environmental conditions, which could enable tea cultivation outside global growing regions. Microsatellite markers are often the best choice for genetic diversity analysis in genebank collections. However, their use in polyploid species is questionable because simple sequence repeat (SSR) allele dosage cannot be readily determined. Therefore, the efficiency of SSR and start codon targeted (SCoT) markers was investigated using 43 selected cultivars from the Russian genebank collection derived from mutant breeding and clonal selection. Previously, the increase in genome size was confirmed in 18 mutants within this collection. Despite the presence of polyploid tea genotypes, our study revealed higher efficiency of SSR markers than SCoT markers. Subsequent SSR analysis of the 106 genotypes in the Russian genebank collection revealed three distinct genetic clusters after STRUCTURE analysis. Greater genetic variation was observed within genetic clusters than between clusters, indicating low genetic variation between collections. Nevertheless, the northernmost tea collection exhibited a greater genetic distance from the other two clusters than they did from each other. Close genetic relationships were found between many cultivars with particularly large leaves and mutant forms. Pearson’s correlation analysis revealed a significant, moderate correlation between genome size and leaf area size. Our study shows that microsatellite fingerprinting is useful to estimate the genetic diversity and genetic background of tea germplasm in Russia despite polyploid tea accessions. Thus, the results of our study contribute to the development of future tea germplasm conservation strategies and modern tea breeding programs.
Practice in Nursery Weed Control—Review and Meta-Analysis
Authors: Yu Ping , Marble Stephen Christopher
Published: February 2022

Weeds, as one of the biggest challenges in the nursery industry, have been controlled by various methods, such as chemical and non-chemical practices. Although these practices have been widely established and tested to control weeds, there is no systematic or meta-analysis review to provide quantitative weed control efficacy information of these practices. To provide a systematic understanding of weed control practices in nursery production, a visualization research trend, a systematic review, and a meta-analysis were conducted. A total of 267 relevant studies were included for the research trend and 83 were included in the meta-analysis. The results in this study showed that interests in nursery weed control have switched dramatically in the past 2–3 decades (1995–2021) from chemical dominant weed control to chemical coexistent with non-chemical techniques. Developing new management tactics and implementing diverse combinations of integrated weed management present the future trend for weed control. The systematic review results showed that chemical methods had the highest weed control efficacy, while non-chemical had the lowest on average, nonetheless, all three weed control practices (chemical, non-chemical, and combined) reduced the weed biomass and density significantly compared with when no strategy was employed. Weed control challenges could be the catalyst for the development of new non-chemical and integrated weed control techniques.
Protein Processing in Plant Mitochondria Compared to Yeast and Mammals
Authors: Heidorn-Czarna Malgorzata , Maziak Agata , Janska Hanna
Published: February 2022

Limited proteolysis, called protein processing, is an essential post-translational mechanism that controls protein localization, activity, and in consequence, function. This process is prevalent for mitochondrial proteins, mainly synthesized as precursor proteins with N-terminal sequences (presequences) that act as targeting signals and are removed upon import into the organelle. Mitochondria have a distinct and highly conserved proteolytic system that includes proteases with sole function in presequence processing and proteases, which show diverse mitochondrial functions with limited proteolysis as an additional one. In virtually all mitochondria, the primary processing of N-terminal signals is catalyzed by the well-characterized mitochondrial processing peptidase (MPP). Subsequently, a second proteolytic cleavage occurs, leading to more stabilized residues at the newly formed N-terminus. Lately, mitochondrial proteases, intermediate cleavage peptidase 55 (ICP55) and octapeptidyl protease 1 (OCT1), involved in proteolytic cleavage after MPP and their substrates have been described in the plant, yeast, and mammalian mitochondria. Mitochondrial proteins can also be processed by removing a peptide from their N- or C-terminus as a maturation step during insertion into the membrane or as a regulatory mechanism in maintaining their function. This type of limited proteolysis is characteristic for processing proteases, such as IMP and rhomboid proteases, or the general mitochondrial quality control proteases ATP23, m-AAA, i-AAA, and OMA1. Identification of processing protease substrates and defining their consensus cleavage motifs is now possible with the help of large-scale quantitative mass spectrometry-based N-terminomics, such as combined fractional diagonal chromatography (COFRADIC), charge-based fractional diagonal chromatography (ChaFRADIC), or terminal amine isotopic labeling of substrates (TAILS). This review summarizes the current knowledge on the characterization of mitochondrial processing peptidases and selected N-terminomics techniques used to uncover protease substrates in the plant, yeast, and mammalian mitochondria.