bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial intelligence platform, RADR®, aids in the discovery of DNA damaging agent for the ultra-rare cancer Atypical Teratoid Rhabdoid Tumors
Authors: McDermott Joseph , Sturtevant Drew , Kathad Umesh , Varma Sudhir , Zhou Jianli , Kulkarni Aditya , Biyani Neha , Schimke Caleb , Reinhold William C. , Elloumi Fathi , Carr Peter , Pommier Yves , Bhatia Kishor
Published: October 2022

Over the last decade the next-generation sequencing and ‘omics techniques have become indispensable tools for medicine and drug discovery. These techniques have led to an explosion of publicly available data that often goes under-utilized due to the lack of bioinformatic expertise and tools to analyze that volume of data. Here, we demonstrate the power of applying two novel computational platforms, the NCI’s CellMiner Cross Database and Lantern Pharma’s proprietary artificial intelligence (AI) and machine learning (ML) RADR® platform, to identify biological insights and potentially new target indications for the acylfulvene derivative drugs LP-100 (Irofulven) and LP-184. Analysis of multi-omics data of both drugs within CellMinerCDB generated discoveries into their mechanism of action, gene sets uniquely enriched to each drug, and how these drugs differed from existing DNA alkylating agents. Data from CellMinerCDB suggested that LP-184 and LP-100 were predicted to be effective in cancers with chromatin remodeling deficiencies, like the ultra-rare and fatal childhood cancer Atypical Teratoid Rhabdoid Tumors (ATRT). Lantern’s AI and ML RADR® platform was then utilized to build a model to test, in silico, if LP-184 would be efficacious in ATRT patients. In silico, RADR® aided in predicting that, indeed, ATRT would be sensitive to LP-184, which was then validated in vitro and in vivo. Applying computational tools and AI, like CellMinerCDB and RADR®, are novel and efficient translational approaches to drug discovery for rare cancers like ATRT.
Novel variant in HHAT as a cause of different sex development with partial gonadal dysgenesis associated with microcephaly, eye defects, and distal phalangeal hypoplasia of both thumbs: Case report
Authors: Baz-Redón Noelia , Soler-Colomer Laura , Fernández-Cancio Mónica , Benito-Sanz Sara , Garrido Marta , Moliné Teresa , Clemente María , Camats-Tarruella Núria , Yeste Diego
Published: October 2022

The palmitoylation of the Hedgehog (Hh) family of morphogens, named sonic hedgehog (SHH), desert hedgehog (DHH), and Indian hedgehog (IHH), is crucial for effective short- and long-range signaling. The hedgehog acyltransferase (HHAT) attaches the palmitate molecule to the Hh; therefore, variants in HHAT cause a broad spectrum of phenotypes. A missense HHAT novel variant c.1001T>A/p.(Met334Lys) was described in a patient first referred for a 46,XY different sexual development with partial gonadal dysgenesis but with microcephaly, eye defects, and distal phalangeal hypoplasia of both thumbs. The in silico analysis of the variant predicted an affectation of the nearest splicing site. Thus, in vitro minigene studies were carried out, which demonstrated that the variant does not affect the splicing. Subsequent protein in silico studies supported the pathogenicity of the variant, and, in conclusion, this was considered the cause of the patient’s phenotype.
Central Asia daily extreme precipitation in observations and gridded datasets: A threshold criteria perspective
Authors: Chen Jing , Yao Junqiang , Dilinuer Tuoliewubieke , Li Jiangang , Li Shujuan , Yang Lianmei , Mao Weiyi
Published: October 2022

The extreme precipitation threshold is fundamental to extreme precipitation research, directly affecting the cognition of extreme characteristics. Based on the daily precipitation data of 62 meteorological stations from 1985 to 2005, this study uses parametric and non-parametric approaches to determine the extreme precipitation threshold in Central Asia, analyzes the statistics and spatial distribution of different threshold criteria, and discusses the trend of extreme precipitation. The capability of the grid dataset of APHRODITE and GPCC in the extreme precipitation analysis in Central Asia is evaluated from the threshold perspective. The results are as follows: 1) Contrary to the parametric approach, the threshold determined by the percentile indices in the warm season is slightly higher than in the cold season. The mean threshold of the warm (cold) season in Central Asia is defined by the 95th percentile index and the 10-year return period, which are 14.0 mm (13.5 mm) and 24.2 mm (25.7 mm), respectively. 2) The spatial distribution of extreme precipitation threshold in Central Asia is higher in the southeast and lower in the north during the cold season; In the warm season, it is high in the north and southwest and low in the center. 3) Although both APHRODITE and GPCC datasets can basically reproduce the spatial distribution of extreme precipitation threshold, they underestimate the magnitude of the threshold, especially APHRODITE. 4) There is no obvious extreme precipitation trend in Central Asia during the study period. Furthermore, the trend in characteristics of extreme precipitation based on different thresholds shows a consistent trend in time but not spatially. We suggest that the threshold selection should adjust the balance between sufficient samples and extreme values according to actual conditions. The results of this study can provide a reference for extreme precipitation threshold criteria under specific application conditions in Central Asia.
A study on dynamic evolution, regional differences and convergence of high-quality economic development in urban agglomerations: A case study of three major urban agglomerations in the Yangtze river economic belt
Authors: Zha Qifen , Liu Zhen , Song Zhihui , Wang Jian
Published: October 2022

Based on the data of 85 cities in the three major urban agglomerations in the Yangtze River Economic Belt from 2011 to 2020, this paper measures the level of high-quality economic development of each city through the improved entropy-weighted TOPSIS method and uses the kernel density estimation method, Dagum Gini coefficient, and convergence model to further study the dynamic evolution, regional differences, and convergence state of the high-quality economic development level of the three major urban agglomerations in the Yangtze River Economic Belt. The study finds that: 1) the high-quality economic development level of each city within the three major urban agglomerations of the Yangtze River Economic Belt has been continuously improved over time, but the development level of each urban agglomeration is not the same; 2) the high-quality economic development level of the three urban agglomerations in the Yangtze River Economic Belt has spatial differences, that is, the high-quality economic development level of the Yangtze River Delta urban agglomeration is better than the two urban agglomerations; 3) the σ convergence and β convergence characteristics exist in the three major urban agglomerations as a whole as well as in each urban agglomeration, and the β convergence rates of the urban agglomerations are not consistent. On the whole, the convergence rate of the middle reaches of the Yangtze River urban agglomeration is the fastest, followed by the Chengdu-Chongqing urban agglomeration, and the Yangtze River Delta urban agglomeration is the slowest. Finally, based on the findings of the study, targeted policy recommendations to promote the high-quality economic development of the three major urban agglomerations in the Yangtze River Economic Belt are proposed.
Promoting systems thinking and pro-environmental policy support through serious games
Authors: Sajjadi Pejman , Bagher Mahda M. , Myrick Jessica G. , Guerriero Joseph G. , White Timothy S. , Klippel Alexander , Swim Janet K.
Published: October 2022

We evaluated whether teaching the public about the “critical zone”–the Earth’s outer skin, critical to all life—via a digital serious game can affect adults’ systems thinking about the environment and support policies to protect the environment. An experiment (N = 152) compared the effects of playing “CZ Investigator” versus viewing a static website on systems thinking about the Food-Energy-Water (FEW) nexus and support for relevant public policies. The serious game had the strongest effects on our outcomes of interest for those participants with less past science education. For these individuals, the serious game, relative to the static website, increased perceptions of the strength of interconnections across food, energy, and water systems (p < .01) and support for policies that regulated human impacts on the environment (p < .01). Mediation analysis revealed that increases in systems thinking explain increases in policy support. This group of users also indicated that the game was easier, more enjoyable, and more effective for learning than the website. Mediation analyses also revealed that perceived learning effectiveness was a stronger mediator than ease and enjoyment effects of the game on systems thinking and policy support. These results are valuable for environmental education because understanding interconnections within complex systems is vital for solving environmental problems, particularly for learners with less background in science.
Evaluating water resources carrying capacity of Pearl River Delta by entropy weight-TOPSIS model
Authors: Zhou Yueying , Liu Zufa , Zhang Bowei , Yang Qiannan
Published: October 2022

To understand the spatio-temporal changes in the water resources carrying capacity (WRCC) of Pearl River Delta (PRD), 19 indicators were selected from three subsystems (water resources, socio-economic, and eco-environment), and the entropy weight-TOPSIS model was employed to analyze the WRCC of each cities in PRD from 2015 to 2020. As the result shows, the water resources subsystem (WRS) had the largest weight in the evaluation system, followed by the socio-economic subsystem (SES), and the eco-environmental subsystem (EES); among these indicators, economic density, water resources per capita, annual precipitation, and new soil erosion treatment area had the highest weights; the PRD had a low WRCC score overall, with considerable regional differences; the capacity score changed with time, but the ranking of cities remained largely the same, with Shenzhen, Zhaoqing, and Huizhou marking higher scores, whereas Zhongshan, Foshan, and Zhuhai achieving lower scores. It was also found that Shenzhen had a high score for SES, which made up for the shortage of natural water resources there; cities like Huizhou, Jiangmen, and Zhaoqing which boast rich water resources and extensive development achieved high scores for WRS and EES. As the PRD develops, it is important to optimize dispatch of water resources, boost green economy, and promote ecological wellbeing.
Water quality monitoring and assessment based on cruise monitoring, remote sensing, and deep learning: A case study of Qingcaosha Reservoir
Authors: Qian Jing , Liu Hongbo , Qian Li , Bauer Jonas , Xue Xiaobai , Yu Gongliang , He Qiang , Zhou Qi , Bi Yonghong , Norra Stefan
Published: October 2022

Accurate monitoring and assessment of the environmental state, as a prerequisite for improved action, is valuable and necessary because of the growing number of environmental problems that have harmful effects on natural systems and human society. This study developed an integrated novel framework containing three modules remote sensing technology (RST), cruise monitoring technology (CMT), and deep learning to achieve a robust performance for environmental monitoring and the subsequent assessment. The deep neural network (DNN), a type of deep learning, can adapt and take advantage of the big data platform effectively provided by RST and CMT to obtain more accurate and improved monitoring results. It was proved by our case study in the Qingcaosha Reservoir (QCSR) that DNN showed a more robust performance (R2 = 0.89 for pH, R2 = 0.77 for DO, R2 = 0.86 for conductivity, and R2 = 0.95 for backscattered particles) compared to the traditional machine learning, including multiple linear regression, support vector regression, and random forest regression. Based on the monitoring results, the water quality assessment of QCSR was achieved by applying a deep learning algorithm called improved deep embedding clustering. Deep clustering analysis enables the scientific delineation of joint control regions and determines the characteristic factors of each area. This study presents the high value of the framework with a core of big data mining for environmental monitoring and follow-up assessment in a manner of high frequency, multidimensionality, and deep hierarchy.
Effectiveness of government environmental auditing in the industrial manufacturing structure upgradation
Authors: Chai Kuang-Cheng , Zhu Jiawei , Lan Hao-Ran , Lu Yujiao , Liu Rui-Yang , Liu Pingshan
Published: October 2022

This paper is based on “Opinion of the Audit-Commission on Strengthening Resource and Environmental Auditing” issued by the Audit Commission in 2009. The commission suggested studies on the impact of industrial structure upgradation in the manufacturing enterprises in China, based on 2006 to 2008 stocks of the listed companies in Shanghai and Shenzhen. Propensity Score Matching (PSM) and Differences-in-Differences (DID) were used to test the induced effect of the policy on industrial structure upgradation by comparing the experimental and control groups before and after policy implementation. The study found that government environmental auditing (GEA) upgrades the structure of the manufacturing industry. The data also reveals that the positive impact of GEA on the upgradation of industrial structure was significantly manifested in state-owned enterprises (SOEs). The findings validate the governance effect of GEA, expand the perspective of industrial structure upgradation in manufacturing enterprises, and provide suggestions on the regulatory effect in the industrial transformation of enterprises.
Exploring spatio-temporal change in global land cover using categorical intensity analysis
Authors: Lamchin Munkhnasan , Bilintoh Thomas Mumuni , Lee Woo-Kyun , Ochir Altansukh , Lim Chul-Hee
Published: October 2022

The rates of land degradation and urbanization has increased worldwide during the past century. Herein, we evaluate the spatio-temporal changes in global land cover via categorical intensity analysis of the European Space Agency’s climate change initiative (ESA-CCI) data for the period 1992 to 2018. Specifically, we evaluated intensity analysis at the category level for five time intervals, namely 1992–1997, 1997–2002, 2002–2007 and 2007–2012, 2012–2018. We also, evaluate the decrease and increase in the land cover at continental and climate zone. The study evaluates the following land cover categories: Cropland, Forest, SGO (Shrubland, Grassland, and Other), Urban, Bare areas, and WIS (Water, ice, and snow). After accuracy assessment, the global land-cover map for 2009 from the GlobCover data is selected, and a reclassified version of this map is used as a verification tool for comparison with the reclassified study data. The analysis of changes over the last 26 years shows that the loss for Cropland are dormant during the first and second time intervals, but active during the third, fourth, and fifth time intervals. By contrast, Forest experienced loss during all time intervals, and SGO experienced active loss only during the second time interval. Urban is the only category that experienced active gain during all time intervals. The present study also indicates that urbanization has and converted land in temperate regions during the past 26 years. Additionally, in South America and the tropical regions, the expansion of Cropland is the largest contributor to the decline in Forests and SGO.
Multiple migrations from East Asia led to linguistic transformation in NorthEast India and mainland Southeast Asia
Authors: Tagore Debashree , Majumder Partha P. , Chatterjee Anupam , Basu Analabha
Published: October 2022

NorthEast India, with its unique geographic location in the midst of the Himalayas and Bay of Bengal, has served as a passage for the movement of modern humans across the Indian subcontinent and East/Southeast Asia. In this study we look into the population genetics of a unique population called the Khasi, speaking a language (also known as the Khasi language) belonging to the Austroasiatic language family and residing amidst the Tibeto-Burman speakers as an isolated population. The Khasi language belongs to one of the three major broad classifications or phyla of the Austroasiatic language and the speakers of the three sub-groups are separated from each other by large geographical distances. The Khasi speakers are separated from their nearest Austroasiatic language-speaking sub-groups: the “Mundari” sub-family from East and peninsular India and the “Mon-Khmers” in Mainland Southeast Asia. We found the Khasi population to be genetically distinct from other Austroasiatic speakers, i.e. Mundaris and Mon-Khmers, but relatively similar to the geographically proximal Tibeto Burmans. The possible reasons for this genetic-linguistic discordance lie in the admixture history of different migration events that originated from East Asia and proceeded possibly towards Southeast Asia. We found at least two distinct migration events from East Asia. While the ancestors of today’s Tibeto-Burman speakers were affected by both, the ancestors of Khasis were insulated from the second migration event. Correlating the linguistic similarity of Tibeto-Burman and Sino-Tibetan languages of today’s East Asians, we infer that the second wave of migration resulted in a linguistic transition while the Khasis could preserve their linguistic identity.
Pembrolizumab in Chinese patients with advanced melanoma: 3-year follow-up of the KEYNOTE-151 study
Authors: Si Lu , Zhang Xiaoshi , Shu Yongqian , Pan Hongming , Wu Di , Liu Jiwei , Mao Lili , Wang Xuan , Wen Xizhi , Gu Yanhong , Zhu Lingjun , Lan Shijie , Cai Xin , Diede Scott J. , Dai Haiyan , Niu Cuizhen , Li Jianfeng , Guo Jun
Published: October 2022

Survival is generally poor for Chinese patients with advanced melanoma because of high rates of acral and mucosal melanoma and limited therapeutic options. The first analysis of the phase 1b KEYNOTE-151 study showed second-line pembrolizumab was well tolerated and had clinically meaningful antitumor activity in Chinese patients with advanced melanoma. Three-year follow-up is presented. Eligible patients were of Chinese descent and had unresectable stage III/IV melanoma that progressed after first-line therapy. Patients received pembrolizumab 2 mg/kg every 3 weeks for ≤35 cycles. Primary end points were safety and objective response rate (ORR). Secondary end points included duration of response (DOR), progression-free survival (PFS), and overall survival (OS). Response was assessed per RECIST v1.1 by blinded independent central review. Subgroup analyses were conducted by melanoma subtype and BRAF and PD-L1 status (acral melanoma only). 103 patients were enrolled; median follow-up duration (time from first dose to data cutoff [July 13, 2020]) was 44.6 months (IQR, 39.1–46.2). Any-grade treatment-related adverse events (TRAEs) occurred in 85.4% of patients, and grade 3/4 TRAEs in 12.6%. No grade 5 TRAEs occurred. Three patients discontinued pembrolizumab because of TRAEs (immune-mediated hepatitis, pneumonia, and arthritis). Immune-mediated AEs and infusion reactions occurred in 34.0% (grade 3/4, 2.9%). ORR was 17.6% (95% CI, 10.8–26.4; 1 complete response/17 partial responses), and median DOR was 13.8 months (range, 2.7–37.4+). Median PFS was 2.8 months (95% CI, 2.7–3.5) and 36-month PFS rate was 5.0%. Median OS was 13.2 months (95% CI, 10.4–16.5) and 36-month OS rate was 22.3%. Median OS for patients with known melanoma subtype was 14.8 months for acral, 13.5 months for nonacral cutaneous, and 7.4 months for mucosal melanoma. Among the acral subgroup, median OS was 22.8 months for PD-L1–positive disease, 8.4 months for PD-L1–negative disease, 18.5 months for BRAF wild-type disease, and 5.8 months for BRAF-mutant disease. Over 3 years’ follow-up, second-line pembrolizumab continued to show manageable safety, clinically meaningful antitumor activity, and durable responses in Chinese patients with advanced melanoma. Subgroup analysis suggested particular benefit in PD-L1–positive and BRAF wild-type acral melanoma, although small subgroup sizes preclude definitive conclusions.

Clinical trial registration

https://clinicaltrials.gov, identifier NCT02821000.
Characterization of immune features and immunotherapy response in subtypes of hepatocellular carcinoma based on mitophagy
Authors: Wang Yanan , Peng Boshizhang , Ning Chun , He Shuya , Yang Huayu , Mao Yilei , Sun Lejia
Published: October 2022

Mitophagy is suggested to be involved in tumor initiation and development; however, mitophagy heterogeneity in hepatocellular carcinoma (HCC) and its association with immune status and prognosis remain unclear. Differentially expressed genes (DEGs) were identified using expression profiles acquired from The Cancer Genome Atlas (TCGA). Mitophagy-related subtypes were identified using the ConsensusClusterPlus software. The differences in prognosis, clinical characteristics, and immune status, including immune cell infiltration, immune function, immune-checkpoint gene expression, and response to immunotherapy, were compared between subtypes. A mitophagy-related gene signature was constructed by applying least absolute shrinkage and selection operator regression to the TCGA cohort. The International Cancer Genome Consortium cohort and the cohort from Peking Union Medical College Hospital were utilized for validation. Carbonyl cyanide m-chlorophenylhydrazone was used to induce mitophagy in HCC cell lines to obtain our own mitophagy signature. Real-time polymerase chain reaction was used for the experimental validation of the expression of model genes. Two mitophagy-related subtypes with distinct prognoses, clinical characteristics, immune states, and biological function patterns were identified based on the mitophagy-related DEGs. The subtype that showed higher mitophagy-related DEG expression had worse survival outcomes, suppressed immune function, higher immune-checkpoint gene expression, and a better response to immunotherapy, indicating that this subpopulation in HCC may benefit from immune-checkpoint blockade therapy and other immunotherapies. A risk model consisting of nine mitophagy-related genes was constructed and its performance was confirmed in two validation cohorts. The risk score was an independent risk factor even when age, sex, and tumor stage were considered. Our study identified two distinct mitophagy subtypes and built a mitophagy signature, uncovering mitophagy heterogeneity in HCC and its association with immune status and prognosis. These findings shed light on the treatment of HCC, especially with immunotherapy.
Devonian upper ocean redox trends across Laurussia: Testing potential influences of marine carbonate lithology on bulk rock I/Ca signals
Authors: He Ruliang , Elrick Maya , Day James , Lu Wanyi , Lu Zunli
Published: October 2022

The Devonian is characterized by major changes in ocean-atmosphere O2 concentrations, colonialization of continents by plants and animals, and widespread marine anoxic events associated with rapid δ13C excursions and biotic crises. However, the long-term upper ocean redox trend for the Devonian is still not well understood. This study presents new I/Ca data from well-dated Lower Devonian through Upper Devonian limestone sections from the Great Basin (western Laurussia) and the Illinois Basin (central Laurussia). In addition, to better address potential influences of lithology and stratigraphy on I/Ca redox signals, I/Ca data are reported here as carbonate lithology-specific. Results indicate that lithologic changes do not exert a dominant control on bulk carbonate I/Ca trends, but the effects of some diagenetic overprints cannot be ruled out. For the Illinois Basin, low I/Ca values (more reducing) are recorded during the Pragian to Emsian and increased but fluctuating values are recorded during the Eifelian to Givetian. The Great Basin I/Ca trends suggest local upper oceans were more reducing in the Lochkovian, more oxic in the Pragian-Emsian, return to more reducing in the Eifelian, then to increasingly more oxic, but fluctuating in the Givetian-Frasnian. The local I/Ca variations at Great Basin likely share more similarity with global upper ocean condition (compared to the Illinois Basin) based on its position adjacent to the Panthalassic Ocean and its temporal co-variation with global environmental volatility trends. The overall reducing and variable redox conditions of local upper ocean (if not a diagenetic signal) during the Middle and Late Devonian of Great Basin coincide with evidence of increased global environmental volatility suggesting seawater redox may have been an important part of environmental instability at this time.
Validation of a simple risk stratification tool for COVID-19 mortality
Authors: Horvath Angela , Lind Theresa , Frece Natalie , Wurzer Herbert , Stadlbauer Vanessa
Published: October 2022

Risk prediction is an essential part of clinical care, in order to allocate resources and provide care appropriately. During the COVID-19 pandemic risk prediction became a matter of political and public debate as a major clinical need to guide medical and organizational decisions. We previously presented a simplified risk stratification score based on a nomogram developed in Wuhan, China in the early phase of the pandemic. Here we aimed to validate this simplified risk stratification score in a larger patient cohort from one city in Austria. Age, oxygen saturation, C-reactive protein levels and creatinine levels were used to estimate the in-hospital mortality risk for COVID-19 patients in a point based score: 1 point per age decade, 4 points for oxygen saturation <92%, 8 points for CRP > 10 mg/l and 4 points for creatinine > 84 μmol/l. Between June 2020 and March 2021, during the “second wave” of the pandemic, 1,472 patients with SARS-CoV-2 infection were admitted to two hospitals in Graz, Austria. In 961 patients the necessary dataset to calculate the simplified risk stratification score was available. In this cohort, as in the cohort that was used to develop the score, a score above 22 was associated with a significantly higher mortality (p < 0.001). Cox regression confirmed that an increase of one point in the risk stratification score increases the 28-day-mortality risk approximately 1.2-fold. Patients who were categorized as high risk (≥22 points) showed a 3–4 fold increased mortality risk. Our simplified risk stratification score performed well in a separate, larger validation cohort. We therefore propose that our risk stratification score, that contains only two routine laboratory parameter, age and oxygen saturation as variables can be a useful and easy to implement tool for COVID-19 risk stratification and beyond. The clinical usefulness of a risk prediction/stratification tool needs to be assessed prospectively (https://www.cbmed.at/covid-19-risk-calculator/).
“Multilocus sequence analysis for population diversity of indigenous entomopathogenic fungus Beauveria bassiana and its bio-efficacy against the cassava mite, Tetranychus truncatus Ehara (Acari: Tetranychidae)”
Authors: Chaithra M. , Prameeladevi T. , Bhagyasree S. N. , Prasad L. , Subramanian S. , Kamil Deeba
Published: October 2022

Beauveria bassiana is an entomopathogenic fungus that causes the white muscadine disease in insects. The majority of entomopathogenic fungi are soil and insect borne, 15 soil samples were collected from seven different locations during 2021, from January to December. Similarly, during 2022, March to December, 15 fungus-infected insect specimens were collected from five different locations hence soil and insect samples from various ecosystems were collected. As a result, 30 B. bassiana isolates from 11 different geographical areas were identified using morphological characteristics and multilocus sequence data in this investigation. The taxonomical positions of the isolates were determined using morphological characteristics and phylogenetic inferences based on three loci (Internal Transcribed Sequence, Elongation Factor-1α, and B. bassiana chitinase 1). In phylogenetic analysis of B. bassiana, the Maximum Likelihood analytical method produced distinct tree topology when compared to Neighbor-joining and minimum evolution. Three isolates viz., Bb3, Bb7 and Bb20 were found closely linked with reference isolate (KTU-24) and other showed the higher population diversity among them. The genetic distances of 30 B. bassiana isolates revealed that 15 were not closely related (D varied from 0.003 to 0.036). The pathogenicity of B. bassiana isolates from various hosts along with one commercial formulation (Beveroz) was assessed against Tetranychus truncatus under in vitro conditions by a completely randomized design (CRD) experiment. The same experiment was repeated thrice to confirm the pathogenicity of B. bassiana against T. truncatus. Later, the collected T. truncatus mortality data was converted into corrected mortality by using the Abbott formula and the values were examined using analysis of variance (ANOVA) in SPSS 23.0 software. Duncan’s Multiple Comparison Test was also done to compare the percentage mortality rates among the 30 B. bassiana isolates. The recorded results showed that the Bb6, Bb15 and Bb12 isolates caused significantly higher mortality of T. truncatus, i.e., 97.73, 96.73 and 94.50% respectively, than the other isolates. This study showed the relativeness among the B. bassiana isolates and establishes their bio-efficacy against T. truncatus, which further can be used for commercialization as bio-pesticide.
Resistance profile and mechanism of severe acute respiratory syndrome coronavirus-2 variants to LCB1 inhibitor targeting the spike receptor-binding motif
Authors: Wu Tong , Zhu Yuanmei , Liu Nian , Hu Yue , Chong Huihui , He Yuxian
Published: October 2022

LCB1 is a 56-mer miniprotein computationally designed to target the spike (S) receptor-binding motif of SARS-CoV-2 with potent in vitro and in vivo inhibitory activities (Cao et al., 2020; Case et al., 2021). However, the rapid emergence and epidemic of viral variants have greatly impacted the effectiveness of S protein-targeting vaccines and antivirals. In this study, we chemically synthesized a peptide-based LCB1 inhibitor and characterized the resistance profile and underlying mechanism of SARS-CoV-2 variants. Among five variants of concern (VOCs), we found that pseudoviruses of Beta, Gamma, and Omicron were highly resistant to the LCB1 inhibition, whereas the pseudoviruses of Alpha and Delta as well as the variant of interest (VOI) Lambda only caused mild resistance. By generating a group of mutant viruses carrying single or combination mutations, we verified that K417N and N501Y substitutions in RBD critically determined the high resistance phenotype of VOCs. Furthermore, a large panel of 85 pseudoviruses with naturally occurring RBD point-mutations were generated and applied to LCB1, which identified that E406Q, K417N, and L455F conferred high-levels of resistance, when Y505W caused a ∼6-fold resistance fold-change. We also showed that the resistance mutations could greatly weaken the binding affinity of LCB1 to RBD and thus attenuated its blocking capacity on the interaction between RBD and the cell receptor ACE2. In conclusion, our data have provided crucial information for understanding the mechanism of SARS-CoV-2 resistance to LCB1 and will guide the design strategy of novel LCB1-based antivirals against divergent VOCs and evolutionary mutants.
Regulation of Nir gene in Lactobacillus plantarum WU14 mediated by GlnR
Authors: Qiu Hulin , Chang Xiaoyu , Luo Yan , Shen Fengfei , Yin Aiguo , Miao Tingting , Li Ying , Xiao Yunyi , Hai Jinping , Xu Bo
Published: October 2022

Nitrogen (N) is an essential element in the biosynthesis of key cellular components, such as proteins and nucleic acids, in all living organisms. Nitrite, as a form of nitrogen utilization, is the main nutrient for microbial growth. However, nitrite is a potential carcinogen that combines with secondary amines, which are breakdown products of proteins, to produce N-nitroso compounds that are strongly carcinogenic. Nitrite reductase (Nir) produced by microorganisms can reduce nitrite. Binding of GlnR to the promoter of nitrogen metabolism gene can regulate the expression of Nir operon. In this study, nitrite-resistant Lactobacillus plantarum WU14 was isolated from Pickles and its protease Nir was analyzed. GlnR-mediated regulation of L. plantarum WU14 Nir gene was investigated in this study. New GlnR and Nir genes were obtained from L. plantarum WU14. The regulation effect of GlnR on Nir gene was examined by gel block test, yeast two-hybrid system, bacterial single hybrid system and qRT-RCR. Detailed analysis showed that GlnR ound to the Nir promoter region and interacted with Nir at low nitrite concentrations, positively regulating the expression of NIR. However, the transcription levels of GlnR and Nir decreased gradually with increasing nitrite concentration. The results of this study improve our understanding of the function of the Nir operon regulatory system and serve as the ground for further study of the signal transduction pathway in lactic acid bacteria.
Quantum-based machine learning and AI models to generate force field parameters for drug-like small molecules
Authors: Mudedla Sathish Kumar , Braka Abdennour , Wu Sangwook
Published: October 2022

Force fields for drug-like small molecules play an essential role in molecular dynamics simulations and binding free energy calculations. In particular, the accurate generation of partial charges on small molecules is critical to understanding the interactions between proteins and drug-like molecules. However, it is a time-consuming process. Thus, we generated a force field for small molecules and employed a machine learning (ML) model to rapidly predict partial charges on molecules in less than a minute of time. We performed density functional theory (DFT) calculation for 31770 small molecules that covered the chemical space of drug-like molecules. The partial charges for the atoms in a molecule were predicted using an ML model trained on DFT-based atomic charges. The predicted values were comparable to the charges obtained from DFT calculations. The ML model showed high accuracy in the prediction of atomic charges for external test data sets. We also developed neural network (NN) models to assign atom types, phase angles and periodicities. All the models performed with high accuracy on test data sets. Our code calculated all the descriptors that were needed for the prediction of force field parameters and produced topologies for small molecules by combining results from ML and NN models. To assess the accuracy of the predicted force field parameters, we calculated solvation free energies for small molecules, and the results were in close agreement with experimental free energies. The AI-generated force field was effective in the fast and accurate generation of partial charges and other force field parameters for small drug-like molecules.
Multi-omics analysis: Paving the path toward achieving precision medicine in cancer treatment and immuno-oncology
Authors: Raufaste-Cazavieille Virgile , Santiago Raoul , Droit Arnaud
Published: October 2022

The acceleration of large-scale sequencing and the progress in high-throughput computational analyses, defined as omics, was a hallmark for the comprehension of the biological processes in human health and diseases. In cancerology, the omics approach, initiated by genomics and transcriptomics studies, has revealed an incredible complexity with unsuspected molecular diversity within a same tumor type as well as spatial and temporal heterogeneity of tumors. The integration of multiple biological layers of omics studies brought oncology to a new paradigm, from tumor site classification to pan-cancer molecular classification, offering new therapeutic opportunities for precision medicine. In this review, we will provide a comprehensive overview of the latest innovations for multi-omics integration in oncology and summarize the largest multi-omics dataset available for adult and pediatric cancers. We will present multi-omics techniques for characterizing cancer biology and show how multi-omics data can be combined with clinical data for the identification of prognostic and treatment-specific biomarkers, opening the way to personalized therapy. To conclude, we will detail the newest strategies for dissecting the tumor immune environment and host–tumor interaction. We will explore the advances in immunomics and microbiomics for biomarker identification to guide therapeutic decision in immuno-oncology.
Predicting clinical response to everolimus in ER+ breast cancers using machine-learning
Authors: Nath Aritro , Cosgrove Patrick A. , Chang Jeffrey T. , Bild Andrea H.
Published: October 2022

Endocrine therapy remains the primary treatment choice for ER+ breast cancers. However, most advanced ER+ breast cancers ultimately develop resistance to endocrine. This acquired resistance to endocrine therapy is often driven by the activation of the PI3K/AKT/mTOR signaling pathway. Everolimus, a drug that targets and inhibits the mTOR complex has been shown to improve clinical outcomes in metastatic ER+ breast cancers. However, there are no biomarkers currently available to guide the use of everolimus in the clinic for progressive patients, where multiple therapeutic options are available. Here, we utilized gene expression signatures from 9 ER+ breast cancer cell lines and 23 patients treated with everolimus to develop and validate an integrative machine learning biomarker of mTOR inhibitor response. Our results show that the machine learning biomarker can successfully distinguish responders from non-responders and can be applied to identify patients that will most likely benefit from everolimus treatment.
The present and future of neural interfaces
Authors: Valeriani Davide , Santoro Francesca , Ienca Marcello
Published: October 2022

The 2020's decade will likely witness an unprecedented development and deployment of neurotechnologies for human rehabilitation, personalized use, and cognitive or other enhancement. New materials and algorithms are already enabling active brain monitoring and are allowing the development of biohybrid and neuromorphic systems that can adapt to the brain. Novel brain-computer interfaces (BCIs) have been proposed to tackle a variety of enhancement and therapeutic challenges, from improving decision-making to modulating mood disorders. While these BCIs have generally been developed in an open-loop modality to optimize their internal neural decoders, this decade will increasingly witness their validation in closed-loop systems that are able to continuously adapt to the user's mental states. Therefore, a proactive ethical approach is needed to ensure that these new technological developments go hand in hand with the development of a sound ethical framework. In this perspective article, we summarize recent developments in neural interfaces, ranging from neurohybrid synapses to closed-loop BCIs, and thereby identify the most promising macro-trends in BCI research, such as simulating vs. interfacing the brain, brain recording vs. brain stimulation, and hardware vs. software technology. Particular attention is devoted to central nervous system interfaces, especially those with application in healthcare and human enhancement. Finally, we critically assess the possible futures of neural interfacing and analyze the short- and long-term implications of such neurotechnologies.
Disruption of white matter integrity and its relationship with cognitive function in non-severe traumatic brain injury
Authors: Abdullah Aimi Nadhiah , Ahmad Asma Hayati , Zakaria Rahimah , Tamam Sofina , Abd Hamid Aini Ismafairus , Chai Wen Jia , Omar Hazim , Abdul Rahman Muhammad Riddha , Fitzrol Diana Noma , Idris Zamzuri , Ghani Abdul Rahman Izaini , Wan Mohamad Wan Nor Azlen , Mustafar Faiz , Hanafi Muhammad Hafiz , Reza Mohamed Faruque , Umar Hafidah , Mohd Zulkifly Mohd Faizal , Ang Song Yee , Zakaria Zaitun , Musa Kamarul Imran , Othman Azizah , Embong Zunaina , Sapiai Nur Asma , Kandasamy Regunath , Ibrahim Haidi , Abdullah Mohd Zaid , Amaruchkul Kannapha , Valdes-Sosa Pedro Antonio , Bringas Vega Maria Luisa , Biswal Bharat , Songsiri Jitkomut , Yaacob Hamwira Sakti , Sumari Putra , Noh Nor Azila , Azman Azlinda , Jamir Singh Paramjit Singh , Abdullah Jafri Malin
Published: October 2022

Background

Impairment in cognitive function is a recognized outcome of traumatic brain injury (TBI). However, the degree of impairment has variable relationship with TBI severity and time post injury. The underlying pathology is often due to diffuse axonal injury that has been found even in mild TBI. In this study, we examine the state of white matter putative connectivity in patients with non-severe TBI in the subacute phase, i.e., within 10 weeks of injury and determine its relationship with neuropsychological scores.

Methods

We conducted a case-control prospective study involving 11 male adult patients with non-severe TBI and an age-matched control group of 11 adult male volunteers. Diffusion MRI scanning and neuropsychological tests were administered within 10 weeks post injury. The difference in fractional anisotropy (FA) values between the patient and control groups was examined using tract-based spatial statistics. The FA values that were significantly different between patients and controls were then correlated with neuropsychological tests in the patient group.

Results

Several clusters with peak voxels of significant FA reductions (p < 0.05) in the white matter skeleton were seen in patients compared to the control group. These clusters were located in the superior fronto-occipital fasciculus, superior longitudinal fasciculus, uncinate fasciculus, and cingulum, as well as white matter fibers in the area of genu of corpus callosum, anterior corona radiata, superior corona radiata, anterior thalamic radiation and part of inferior frontal gyrus. Mean global FA magnitude correlated significantly with MAVLT immediate recall scores while matrix reasoning scores correlated positively with FA values in the area of right superior fronto-occipital fasciculus and left anterior corona radiata.

Conclusion

The non-severe TBI patients had abnormally reduced FA values in multiple regions compared to controls that correlated with several measures of executive function during the sub-acute phase of TBI.
Clinical comparison of two automated audiometry procedures
Authors: Liu Hui , Du Bingqing , Liu Bo , Fu Xinxing , Wang Yao
Published: October 2022

Objective

Automated pure-tone audiometry has been shown to provide similar hearing threshold estimates to conventional audiometry, but lower correlations were reported at high and low frequencies in audiometric tests than those of manual tests, while the correlations were better in the middle frequencies. In this paper, we used the same equipment and different test procedures for automated testing, and compared the results with manual test results.

Design

One hundred subjects aged 18–36 years were randomly divided into two groups to perform air-conduction pure-tone audiometry (0.25, 0.5, 1, 2, 4, 8 kHz) using the ascending and shortened ascending protocols built-in to the automated audiometer, respectively. Recorded testing time, the total number of responses and the subject’s preference tests were compared with those of manual tests.

Results

Significant difference was found at 250 Hz regarding the distribution of the absolute difference between the two automated and the manual thresholds. The testing time spend in the ascending method (9.8 ± 1.4 min, mean ± SD) was significantly longer than in the shorted ascending method (5.8 ± 0.9 min). The total numbers of responses of the ascending method (90.5 ± 10.8 times) and shorted ascending method (62.0 ± 11.4 times) were significantly different. Finally, no significant difference was found in preferences between automated and manual procedures.

Conclusion

The shorted ascending method can save lots of testing time. The difference between the two automated thresholds at 250 Hz is caused by the different test procedures, and the difference at 8,000 Hz between the automated test and the manual test can be due to the transducer types and allowable differences in calibration.
Apoptosis-associated speck-like protein containing a CARD-mediated release of matrix metalloproteinase 10 stimulates a change in microglia phenotype
Authors: Sánchez Kathryn E. , Bhaskar Kiran , Rosenberg Gary A.
Published: October 2022

Inflammation contributes to amyloid-β and tau pathology in Alzheimer’s disease (AD). Microglia facilitate an altered immune response that includes microgliosis, upregulation of inflammasome proteins, and elevation of matrix-metalloproteinases (MMPs). Studies of cerebrospinal fluid (CSF) and blood in dementia patients show upregulation of two potential biomarkers of inflammation at the cellular level, MMP10 and apoptosis-associated speck-like protein containing a CARD (ASC). However, little is known about their relationship in the context of brain inflammation. Therefore, we stimulated microglia cultures with purified insoluble ASC speck aggregates and MMP10 to elucidate their role. We found that ASC specks altered microglia shape and stimulated the release of MMP3 and MMP10. Furthermore, MMP10 stimulated microglia released additional MMP10 along with the inflammatory cytokines, tumor-necrosis factor-α (TNFα), Interleukin 6 (IL-6), and CXCL1 CXC motif chemokine ligand 1 (CXCL1). A broad-spectrum MMP inhibitor, GM6001, prevented TNFα release. With these results, we conclude that MMP10 and ASC specks act on microglial cells to propagate inflammation.
Effect of 60Co γ-rays on dried figs adsorption isotherms and thermodynamic properties
Authors: Irchad Ahmed , Razouk Rachid , Ouaabou Rachida , Mouhib Mohamed , Hssaini Lahcen
Published: October 2022

Irradiation is one of the promising food preservation techniques, but few are known about its impact on foods' water vapor change. In this research, the impact of gamma irradiation on moisture adsorption isotherms of dried figs, one of the most emblematic foods of the Mediterranean diet, at increasing doses (0, 1, 1.5, and 2 kGy) was investigated. The isotherms data of equilibrium points displayed a sigmoid-shaped curve of the type II pattern for both controlled and irradiated dried figs, with a notable effect of irradiation on equilibrium moisture content, which revealed a decreasing pattern as irradiation dose and temperature increase. This effect was also seen in data fitting, where GAB model showed the best prediction statistics for control samples, while Peleg model displayed the most suitable samples irradiated at 1 and 1.5 kGy, then the Enderby model for those treated with 2 kGy. Results of Net isosteric heat of adsorption suggested that high irradiation dose increases the spontaneity of moisture adsorption. Hence, gamma irradiation exhibited a significant effect on the water-specific surface area of which the magnitude was proportional to the increasingly applied doses. This effect was also visibly significant on the optimum water activity [aw(op)] for proper dried fig storage. Indeed, awwas about 0.4243 for control samples, which is much higher compared to irradiated ones (aw= 0.2). Information from this research suggests that gamma irradiation at a dose up to 2 kGy extended the dried figs' shelf life. Since many aspects related to the impact of gamma irradiation on the moisture adsorption isotherms and thermodynamic properties of dried figs as well as in other foods have yet to be further investigated, this study provides interesting results that may be a useful reference for future research direction.