bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of predictive selection of LbCas12a CRISPR RNAs upon on‐ and off‐target editing rates in soybean
Authors: Rymarquis Linda , Wu Chenxi , Hohorst Diane , Vega‐Sanchez Miguel , Mullen Thomas E. , Vemulapalli Vijetha , Smith Douglas R. 
Published: August 2024

AbstractClustered regularly interspaced short palindromic repeats (CRISPR) technology has revolutionized creating targeted genetic variation in crops. Although CRISPR enzymes have been reported to have high sequence‐specificity, careful design of the editing reagents can also reduce unintended edits at highly homologous sites. This work details the first large‐scale study of the heritability of on‐target edits and the rate of edits at off‐target sites in soybean (Glycine max), assaying ~700 T1 plants each resulting from transformation with LbCas12a constructs containing CRISPR RNAs (crRNAs) predicted to be either “unique” with no off‐target sites or “promiscuous” with >10 potential off‐targets in the soybean genome. Around 80% of the on‐target edits observed in T0 plants were inherited in the T1 generation, and ~49% of the total observed on‐target edits in T1 were not observed at T0, indicating continued activity of LbCas12a throughout the life cycle of the plant. In planta editing at off‐target sites was observed for the Promiscuous but not the Unique crRNA. Examination of the edited off‐target sites revealed that LbCas12a was highly tolerant to mismatches between the crRNA and target site in bases 21–23 relative to the start of the protospacer, but even a single mismatch in the first 20 nt drastically reduced the editing rate. In addition, edits at off‐target sites have lower inheritance rates than on‐target edits, suggesting that they occur later in the plant's lifecycle. Plants with a desired on‐target edit and no off‐target edits could be identified in the T1 generation for 100% of the T0 plants edited with the Unique crRNA compared with the 65% of T0 plants edited with the Promiscuous crRNA. This confirms that proper crRNA selection can reduce or eliminate off‐target editing. Even when potential off‐target sites are predicted, plants containing only the intended edits can still be identified and propagated.
Combining artificial intelligence and conventional statistics to predict bronchopulmonary dysplasia in very preterm infants using routinely collected clinical variables
Authors: Montagna Sara , Magno Dalila , Ferretti Stefano , Stelluti Michele , Gona Andrea , Dionisi Camilla , Simonazzi Giuliana , Martini Silvia , Corvaglia Luigi , Aceti Arianna 
Published: August 2024

AbstractBackgroundPrematurity is the strongest predictor of bronchopulmonary dysplasia (BPD). Most previous studies investigated additional risk factors by conventional statistics, while the few studies applying artificial intelligence, and specifically machine learning (ML), for this purpose were mainly targeted to the predictive ability of specific interventions. This study aimed to apply ML to identify, among routinely collected data, variables predictive of BPD, and to compare these variables with those identified through conventional statistics.MethodsVery preterm infants were recruited; antenatal, perinatal, and postnatal clinical data were collected. A BPD prediction model was built using conventional statistics, and nine supervised ML algorithms were applied for the same purpose: the results of the best‐performing model were described and compared with those of conventional statistics.ResultsBoth conventional statistics and ML identified the degree of immaturity (low gestational age and/or birth weight), need for mechanical ventilation, and absent or reversed end diastolic flow (AREDF) in the umbilical arteries as risk factors for BPD. Each of the two approaches also identified additional potentially predictive clinical variables.ConclusionML algorithms might be useful to integrate conventional statistics in identifying novel risk factors, in addition to prematurity, for the development of BPD in very preterm infants. Specifically, the identification of AREDF status as an independent risk factor for BPD by both conventional statistics and ML highlights the opportunity to include detailed antenatal information in clinical predictive models for neonatal diseases.
Mispacking of the F87 sidechain drives aggregation‐promoting conformational fluctuations in the subunit interfaces of the transthyretin tetramer
Authors: Sun Xun , Ferguson James A. , Yang Ke , Stanfield Robyn L. , Dyson H. Jane , Wright Peter E. 
Published: August 2024

AbstractAberrant formation and deposition of human transthyretin (TTR) aggregates causes transthyretin amyloidosis. To initialize aggregation, transthyretin tetramers must first dissociate into monomers that partially unfold to promote entry into the aggregation pathway. The native TTR tetramer (T) is stabilized by docking of the F87 sidechain into an interfacial cavity enclosed by several hydrophobic residues including A120. We have previously shown that an alternative tetramer (T*) with mispacked F87 sidechains is more prone to dissociation and aggregation than the native T state. However, the molecular basis for the reduced stability in T* remains unclear. Here we report characterization of the A120L mutant, where steric hindrance is introduced into the F87 binding site. The x‐ray structure of A120L shows that the F87 sidechain is displaced from its docking site across the subunit interface. In A120S, a naturally occurring pathogenic mutant that is less aggregation‐prone than A120L, the F87 sidechain is correctly docked, as in the native TTR tetramer. Nevertheless, 19F‐NMR aggregation assays show an elevated population of a monomeric aggregation intermediate in A120S relative to a control containing the native A120, due to accelerated tetramer dissociation and slowed monomer tetramerization. The mispacking of the F87 sidechain is associated with enhanced exchange dynamics for interfacial residues. At 298 K, the T* populations of various naturally occurring mutants fall between 4% and 7% (ΔG ~ 1.5–1.9 kcal/mol), consistent with the free energy change expected for undocking and solvent exposure of one of the four F87 sidechains in the tetramer (ΔG ~ 1.6 kcal/mol). Our data provide a molecular‐level picture of the likely universal F87 sidechain mispacking in tetrameric TTR that promotes interfacial conformational dynamics and increases aggregation propensity.
ARCIMBOLDO at low resolution: Verification for coiled coils and globular proteins
Authors: Caballero Iracema , Castellví Albert , Triviño Josep , Jiménez Elisabet , Soler Nicolas , Borges Rafael Junqueira , Usón Isabel 
Published: August 2024

AbstractCrystallography at low resolution must determine the atomic model from less experimental observations, which is challenging in the absence of a model. In addition, model bias is more severe when independent experimental data are scarce. Our methods solve the phase problem by combining the location of accurate model fragments using Phaser with density modification and interpretation of the resulting maps using SHELXE. From a partial, correct structure, the density modification process and the stereochemical constraints draw the rest of the structure, validating the result. This same principle is now exploited at low resolution. Coiled coils are important, ubiquitous structures but notoriously difficult to phase and to predict. Both correct solutions and incorrect ones are poorly discriminated by the crystallographic figures of merit as long as helices are correctly oriented. We incorporate coiled‐coil verification, designed to set up competing, incompatible structural hypotheses to probe both the results and establish the power of the data to discriminate them. Efficiency of coiled‐coil phasing and validation in test cases from 3 to 4 Å is demonstrated in ARCIMBOLDO_LITE, placing single helices, and in ARCIMBOLDO_SHREDDER, with fragments derived from AlphaFold models. SHELXE tracing at low resolution has been enhanced, maintaining its local character but extending the environment assessment. For non‐helical structures, verification is demonstrated in the fragment location process. Its use is exemplified with the solution of the VSR1 structure at 3.5 Å, depending on LLG optimization and the emergence of new features in the electron density. Relying on verification, we have extended the use of the ARCIMBOLDO software to low resolution.
Structural basis for substrate flexibility of the O‐methyltransferase MpaG' involved in mycophenolic acid biosynthesis
Authors: You Cai , Pan Yunjun , Liu Ruxin , Li Shengying , Feng Yingang 
Published: August 2024

AbstractMpaG' is an S‐adenosyl‐L‐methionine (SAM)‐dependent methyltransferase involved in the compartmentalized biosynthesis of mycophenolic acid (MPA), a first‐line immunosuppressive drug for organ transplantations and autoimmune diseases. MpaG' catalyzes the 5‐O‐methylation of three precursors in MPA biosynthesis including demethylmycophenolic acid (DMMPA), 4‐farnesyl‐3,5‐dihydroxy‐6‐methylphthalide (FDHMP), and an intermediate containing three fewer carbon atoms compared to FDHMP (FDHMP‐3C) with different catalytic efficiencies. Here, we report the crystal structures of S‐adenosyl‐L‐homocysteine (SAH)/DMMPA‐bound MpaG', SAH/FDHMP‐3C‐bound MpaG', and SAH/FDHMP‐bound MpaG' to understand the catalytic mechanism of MpaG' and structural basis for its substrate flexibility. Structural and biochemical analyses reveal that MpaG' utilizes the catalytic dyad H306‐E362 to deprotonate the C5 hydroxyl group of the substrates for the following methylation. The three substrates with differently modified farnesyl moieties are well accommodated in a large semi‐open substrate binding pocket with the orientation of their phthalide moiety almost identical. Based on the structure‐directed mutagenesis, a single mutant MpaG'Q267A is engineered with significantly improved catalytic efficiency for all three substrates. This study expands the mechanistic understanding and the pocket engineering strategy for O‐methyltransferases involved in fungal natural product biosynthesis. Our research also highlights the potential of O‐methyltransferases to modify diverse substrates by protein design and engineering.
Validation of candidate protein biomarkers previously identified by genetic instruments for prostate cancer risk: A prospective cohort analysis of directly measured protein levels in the ARIC study
Authors: Liu Tanxin , Joshu Corinne E. , Lu Jiayun , Prizment Anna , Chatterjee Nilanjan , Wu Lang , Platz Elizabeth A. 
Published: August 2024

AbstractBackgroundMultiple novel protein biomarkers have been shown to be associated with prostate cancer risk using genetic instruments. This study aimed to externally validate the associations of 30 genetically predicted candidate proteins with prostate cancer risk using aptamer‐based levels in US Black and White men in the Atherosclerosis Risk in Communities (ARIC) study. Plasma protein levels were previously measured by SomaScan® using the blood collected in 1990–1992.MethodsAmong 4864 eligible participants, we ascertained 667 first primary prostate cancer cases through 2015. Hazard ratios (HRs) of prostate cancer and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression for tertiles of each protein. We adjusted for age, race, and other risk factors.ResultsOf the 30 proteins and considering a nominal p trend < 0.05, two were positively associated with prostate cancer risk—RF1ML (tertile 3 vs. 1: HR = 1.23; 95% CI 1.02–1.48; p trend = 0.037) and TPST1 (1.28, 95% CI 1.06–1.55; p trend = 0.0087); two were inversely associated—ATF6A (HR = 0.80, 95% CI 0.65–0.98; p trend = 0.028) and SPINT2 (HR = 0.74, 95% CI 0.61–0.90; p trend = 0.0025). One protein, KDEL2, which was nonlinearly associated (test‐for‐linearity: p < 0.01) showed a statistically significant lower risk in the second tertile (HR = 0.79, 95% CI 0.65–0.95). Of these five, four proteins—ATF6A, KDEL2, RF1ML, and TPST1—were consistent in the direction of association with the discovery studies.ConclusionThis study validated some pre‐diagnostic protein biomarkers of the risk of prostate cancer.
The role of gastrodin in the management of CNS‐related diseases: Underlying mechanisms to therapeutic perspectives
Authors: He Xirui , Chen Xufei , Yang Yan , Gu Jingyi , Xie Yulu , Liu Yujie , Hao Man , Heinrich Michael 
Published: August 2024

AbstractCentral nervous system (CNS)‐related diseases have a high mortality rate, are a serious threat to physical and mental health, and have always been an important area of research. Gastrodin, the main active metabolite of Gastrodia elata Blume, used in Chinese medicine and food, has a wide range of pharmacological effects, mostly related to CNS disorders. This review aims to systematically summarize and discuss the effects and underlying mechanisms of gastrodin in the treatment of CNS diseases, and to assess its potential for further development as a lead drug in both biomedicine and traditional Chinese medicine. Studies on the pharmacological effects of gastrodin on the CNS indicate that it may exert anti‐neurodegenerative, cerebrovascular protective, and ameliorative effects on diabetic encephalopathy, perioperative neurocognitive dysfunction, epilepsy, Tourette's syndrome, depression and anxiety, and sleep disorders through various mechanisms. To date, 110 gastrodin products have been approved for clinical use, but further multicenter clinical case–control studies are relatively scarce. Preclinical studies have confirmed that gastrodin can be used to treat CNS‐related disorders. However, important concerns need to be addressed in the context of likely non‐specific, assay interfering effects when gastrodin is studied using in vitro and in silico approaches, calling for a systematic assessment of the evidence to date. High‐quality clinical trials should have priority to evaluate the therapeutic safety and clinical efficacy of gastrodin. Further experimental research using appropriate in vivo models is also needed, focusing on neurodegenerative diseases, cerebral ischemic and hypoxic diseases, brain damage caused by methamphetamine or heavy metals, and epilepsy.
Synthesis of Novel Nanomaterials Based on FeIIICoII and FeIIINiII Mixed Oxides: Characterization and Tribological Performance
Authors: Dzhardimalieva Gulzhian I. , Kugabaeva Gulsara D. , Kydralieva Kamila A. , Drogan Ekaterina G. , Zabiyaka Igor Yu. , Burlakova Victoria E. , Uflyand Igor E. 
Published: August 2024

AbstractIn this work, nanomaterials based on FeIIICoII and FeIIINiII mixed oxides were obtained for the first time by thermal decomposition of polymer complexes of Fe and Co or Ni nitrates with acrylamide. During thermolysis, core‐shell nanomaterials are formed containing nanoparticles of FeCo and FeNi oxides uniformly distributed inside the carbon layer. These nanomaterials are characterized by high chemical and thermal stability. During thermolysis, nanoparticles of mixed oxides FeCo and FeNi were formed with an average crystallite size of 13–22 and 22–33 nm, respectively. Nanomaterials were tested as antifriction and antiwear additives to liquid industrial oil I‐20 A. The values of the friction coefficient decrease by more than 60 % when CoO⋅Fe2O3 with a concentration of 0.05 % is added to the industrial oil I‐20 A.
Synthesis, In Vitro Enzymatic Inhibition, and Molecular Modeling of Novel Piperazine‐Based Bis‐Schiff Base Derivatives as Promising Anti‐urease Agents
Authors: Masood Najat , Hussain Rafaqat , Khan Shoaib , Rahim Fazal , Mumtaz Sundas , Taha Muhammad , Ur Rahman Abid Obaid , Iqbal Tayyiaba , Adnan Ali Shah Syed , Omar Al Wesabi Esam , Magam Seami M. 
Published: August 2024

AbstractThe current study was aimed to synthesize piperazine‐based bis‐Schiff base derivatives (1–15) and were also screened in vitro for their inhibition against urease enzyme under the positive control of thiourea drug (IC50 value of 36.40±2.35 μM). Among the tested analogs, the maximum potency was shown by analog 2 with the lowest IC50 value of 2.10±1.10 μM, whereas the minimum activity was demonstrated by the scaffold 5 having an IC50 value of 49.60±6.10 μM. The experimental results of urease activity prompted us to investigate and propose a possible mechanism of how actives analogs of piperazine derivatives will interacts with the catalytic sites of targeted urease enzymes. For this purpose, molecular docking with Auto Dock Vina gave us an insight into the binding interactions of the active compounds to different amino acid residues of the targeted urease enzyme.
Machine Learning Aided De Novo Design Identifies Novel Benzimidazolone Based Inhibitor‐Modulators for Heat Shock Protein 90 (HSP90)
Authors: Bhowmick Shovonlal , Malhotra Jagriti , Choudhary Rinku , Dilip Shinde Omkar , Metwally Ahmed Sayed M. , Chunarkar Patil Pritee 
Published: August 2024

AbstractThe present study investigates the identification of novel heat shock protein‐90 (HSP90) inhibitors‐modulators employing de novo drug design methodologies. Precisely, a machine learning (ML) assisted de novo design tool, REINVENT4, was employed for generating novel molecules against a given set of known HSP90 inhibitors. Further, a series of cheminformatics analyses were undertaken to assess pharmacokinetic properties, evaluate binding affinity using docking, and predict absolute binding affinity using the KDeep tool to reduce the chemical space. Finally, three novel benzimidazole‐based drug‐like candidates viz. IM1, IM2, and IM3 were selected as potent inhibitors‐modulators for HSP90 protein. Docking‐based binding affinity of IM1, IM2, and IM3 was obtained as −11.30, −11.50, and −11.20 kcal/mol, respectively. Moreover, all identified protein‐ligand complex dynamic behavior has been extensively assessed through MD simulation for a 100 ns span, highlighting overall interaction stability and conformational rearrangements for protein bound with all selected compounds. The MM‐GBSA‐based binding free energy estimation for each complex demonstrated the superiority of identified compounds, as found to be −43.54, −38.34, and −25.50 kcal/mol for IM1, IM2, and IM3. Collectively, pharmacokinetics and drug‐like profile assessment of identified compounds, along with simulation trajectories, explained the potentiality of the compounds for modulating the activity of the HSP90.
Cdo‐Zno Nanocomposite for Efficient Dye Degradation, Sensitive Nitrite Detection, Potential Luminescence and Antioxidant Properties
Authors: Nethravathi P. C. , Gayathri Devi V. , Tejaswini K. C. , Suresh D. 
Published: August 2024

AbstractEnvironmental remediation evinces sensitive detection and elimination of contaminants from the environment. Recent investigations delineate nanomaterials as potentially useful agents in environment remediation. In this investigation, we have developed multifunctional CdO‐ZnO nanocomposite (NCs) for efficient degradation of organic dyes and sensitive detection of nitrite ions which also exhibits excellent luminescence and antioxidant properties. The CdO‐ZnO NCs were developed through a facile method which improved the yield quantity by decreasing the energy consumption there by reducing the cost. Thus synthesized CdO‐ZnO NCs were characterized through X‐ray diffraction, FT‐IR, SEM, TEM, EDX studies. These studies confirmed the successful formation of CdO‐ZnO composite and the average particle size of the NCs was found to be ~50 nm. Selective reduction of harmful industrial organic dyes from the water bodies is one of the important aspects of water pollution. As prepared CdO‐ZnO NCs degraded the MB dye completely in 30 min under visible light irradiation. The effect of various parameters such as catalytic load, dye concentration and pH on the degradation of dye was assessed and the NCs exhibited maximum degradation efficiency at 25 mg of catalytic load and alkaline pH of 11. The photoluminescence studies reveal that the NCs have inherent excellent luminescence property by exhibiting the emission band at 277 and 282 nm. From electrochemical studies, the CdO‐ZnO NCs proclaimed magnificent nitrite sensing property with the LOD value of 9.8 μM. Additionally, antioxidant studies disclosed that NCs remarkably scavenged the DPPH free radicals with IC50 value of 249 μg/mL. Thus, this study establishes simple method for the development of efficient mixed oxide material CdO‐ZnO for multifunctional properties that could find industrial applications.
Nanoscale Mechanical Manipulation of Ultrathin SiN Membranes Enabling Infrared Near‐Field Microscopy of Liquid‐Immersed samples
Authors: Baù Enrico , Gölz Thorsten , Benoit Martin , Tittl Andreas , Keilmann Fritz 
Published: August 2024

AbstractScattering scanning near‐field optical microscopy (s‐SNOM) is a powerful technique for mid‐infrared spectroscopy at nanometer length scales. By investigating objects in aqueous environments through ultrathin membranes, s‐SNOM has recently been extended toward label‐free nanoscopy of the dynamics of living cells and nanoparticles, assessing both the optical and the mechanical interactions between the tip, the membrane and the liquid suspension underneath. Here, the study reports that the tapping AFM tip induces a reversible nanometric deformation of the membrane manifested as either an indentation or protrusion. This mechanism depends on the driving force of the tapping cantilever, which is exploited to minimize topographical deformations of the membrane to improve optical measurements. Furthermore, it is shown that the tapping phase delay between driving signal and tip oscillation is a highly sensitive observable to study the mechanics of adhering objects, exhibiting highest contrast at low tapping amplitudes where the membrane remains nearly flat. Mechanical responses are correlated with simultaneously recorded spectroscopy data to reveal the thickness of nanometric water layers between membrane and adhering objects. Besides a general applicability of depth profiling, the technique holds great promise for studying mechano‐active biopolymers and living cells, biomaterials that exhibit complex behaviors when under a mechanical load.
On‐Demand Picoliter‐Level‐Droplet Inkjet Printing for Micro Fabrication and Functional Applications
Authors: You Kejia , Wang Zhen , Lin Jiasong , Guo Xuan , Lin Liangxu , Liu Yang , Li Fushan , Huang Wei 
Published: August 2024

AbstractWith the advent of Internet of Things (IoTs) and wearable devices, manufacturing requirements have shifted toward miniaturization, flexibility, environmentalization, and customization. Inkjet printing, as a non‐contact picoliter‐level droplet printing technology, can achieve material deposition at the microscopic level, helping to achieve high resolution and high precision patterned design. Meanwhile, inkjet printing has the advantages of simple process, high printing efficiency, mask‐free digital printing, and direct pattern deposition, and is gradually emerging as a promising technology to meet such new requirements. However, there is a long way to go in constructing functional materials and emerging devices due to the uncommercialized ink materials, complicated film‐forming process, and geometrically/functionally mismatched interface, limiting film quality and device applications. Herein, recent developments in working mechanisms, functional ink systems, droplet ejection and flight process, droplet drying process, as well as emerging multifunctional and intelligence applications including optics, electronics, sensors, and energy storage and conversion devices is reviewed. Finally, it is also highlight some of the critical challenges and research opportunities. The review is anticipated to provide a systematic comprehension and valuable insights for inkjet printing, thereby facilitating the advancement of their emerging applications.