Energy balance and global warming potential of corn straw-based bioethanol in China from a life cycle perspective

<p>As the second largest corn producer in this world, China has abundant corn straw resources. The study assessed the energy balance and global warming potential of corn straw-based bioethanol production and utilization in China from a life cycle perspective. The results revealed that bioethanol used as gasoline and diesel blend fuel could reduce global warming potential by 10%–97% and 4%–96%, respectively, as compared to gasoline and diesel for transport. The total global warming potential, net global warming potential, net energy, and Net Energy Ratio per MJ ethanol generated from corn straw-based bioethanol system are estimated to be 0.20 kg CO₂-eq, 0.012 kg CO₂-eq, 0.60 MJ, and 1.87, respectively. By using sensitivity analysis, we found that the collected coefficient and compressing density of straw have a more obvious influence on energy balance; transportation distance has a more obvious influence on global warming potential emission factor. The by-products may be utilized as fertilizer, animal feed, cement replacement, or high-value lignin chemicals, which make a contribution to offsetting 0.28 MJ per MJ ethanol of energy consumption.</p

Nocarbenzoxazoles A–G, Benzoxazoles Produced by Halophilic Nocardiopsis lucentensis DSM 44048

Seven new benzoxazole derivatives, nocarbenzoxazoles A–G (<b>1</b>–<b>7</b>), were isolated from the halophilic strain Nocardiopsis lucentensis DSM 44048. Their structures were elucidated on the basis of 1D and 2D NMR spectroscopic data, HRESIMS, and X-ray single-crystal diffraction. The isolated compounds were assayed for their cytotoxicity against a panel of human tumor cell lines (HepG2, MDA-MB-231, MDA-MB-435, HeLa, and PC3). Compounds <b>1</b>–<b>6</b> were found to have modest or no activity. Compound <b>7</b> showed selective activity against HepG2 and HeLa with IC₅₀ values of 3 and 1 μM, respectively

Porphyrin-Based Porous Organic Frameworks as a Biomimetic Catalyst for Highly Efficient Colorimetric Immunoassay

Herein, we synthesized a cost-effective iron porphyrin (FePor)-based covalent organic polymer (COP), FePor-TFPA-COP, through an easy aromatic substitution reaction between pyrrole and tris­(4-formylphenyl)­amine (TFPA). The triangular pyramid-shaped, N-centric structure of TFPA facilitated the formation of FePor-TFPA-COP with three-dimensional porous structure, larger surface area, and abundant surface catalytically active sites. FePor-TFPA-COP exhibited strong intrinsic peroxidase activity toward a classical peroxidase substrate, 3,3′,5,5′-tetramethylbenzidine (TMB), in the presence of H₂O₂. Compared with horseradish peroxidase (HRP), FePor-TFPA-COP exhibited several advantages such as easy storage, high sensitivity, and prominently chemical and catalytic stability under the harsh conditions, which guaranteed the accuracy and reliability of measurements. Utilizing the excellent catalytic activity, a FePor-TFPA-COP-based colorimetric immunoassay was first established for α-fetoprotein (AFP) detection and showed high sensitivity, stability, and acceptable reproducibility. The linear response range for AFP was 5 pg/mL to 100 ng/mL and the detection limitation was 1 pg/mL. The routine provided a brilliant biomimetic catalyst to develop the nonenzyme immunoassay. More importantly, the high chemical and catalytic stability and sensitivity facilitated future practical applications under various conditions

A new Jehol enantiornithine bird with three-dimensional preservation and ovarian follicles

<p>We report a new enantiornithine bird, <i>Linyiornis amoena</i> gen. et sp. nov., from the Lower Cretaceous Jiufotang Formation in northeastern China. Traces of ovarian follicles indicate that the specimen represents a female individual. The nearly three-dimensional preservation of the new specimen reveals morphological details rarely visible in other Early Cretaceous enantiornithines, allowing more detailed comparison with Late Cretaceous enantiornithines. Differences in the preserved morphology of the right and left coracoids suggest that the appearance of some features is strongly affected by preservation, indicating that the distribution of these features in compressed specimens may need to be reevaluated. Like Late Cretaceous enantiornithine specimens, the holotype of <i>Linyiornis amoena</i> preserves a hypertrophied pit for muscle attachment on the bicipital crest but clearly did not preserve a fossa for the capital ligament, present in Late Cretaceous taxa; we discuss the functional morphology and implications of these features in <i>Linyiornis amoena</i>.</p> <p>http://zoobank.org/urn:lsid:zoobank.org:pub:EFFD4348-7376-4201-A948-CEC686E2E0DC</p> <p>SUPPLEMENTAL DATA—Supplemental materials are available for this article for free at www.tandfonline.com/UJVP</p> <p>Citation for this article: Wang, Y., M. Wang, J. K. O'Connor, X. Wang, X. Zheng, and X. Zhang. 2016. A new Jehol enantiornithine bird with three-dimensional preservation and ovarian follicles. Journal of Vertebrate Paleontology. DOI: 10.1080/02724634.2015.1054496.</p

Enantioselective Synthesis of 4-Substituted 4,5-Dihydro-1<i>H</i>-[1,5]benzodiazepin-2(3<i>H</i>)-ones by the Lewis Base-Catalyzed Hydrosilylation

Enantioselective synthesis of 4-substituted 4,5-dihydro-1<i>H</i>-[1,5]­benzodiazepin-2­(3<i>H</i>)-ones has been accomplished through chiral Lewis base-catalyzed hydrosilylation. The corresponding products were obtained in excellent yields (up to 99%) and enantioselectivities (up to 98%). The absolute configuration of product <b>3n</b> has been determined as <i>S</i> by X-ray crystallographic analysis

Data_Sheet_1_Development and validation of a nomogram based on lymphocyte subsets to distinguish bipolar depression from major depressive disorder.docx

ObjectiveBipolar depression (BD) and major depressive disorder (MDD) are both common affective disorders. The common depression episodes make it difficult to distinguish between them, even for experienced clinicians. Failure to properly diagnose them in a timely manner leads to inappropriate treatment strategies. Therefore, it is important to distinguish between BD and MDD. The aim of this study was to develop and validate a nomogram model that distinguishes BD from MDD based on the characteristics of lymphocyte subsets.Materials and methodsA prospective cross-sectional study was performed. Blood samples were obtained from participants who met the inclusion criteria. The least absolute shrinkage and selection operator (LASSO) regression model was used for factor selection. A differential diagnosis nomogram for BD and MDD was developed using multivariable logistic regression and the area under the curve (AUC) with 95% confidence interval (CI) was calculated, as well as the internal validation using a bootstrap algorithm with 1,000 repetitions. Calibration curve and decision curve analysis (DCA) were used to evaluate the calibration and clinical utility of the nomogram, respectively.ResultsA total of 166 participants who were diagnosed with BD (83 cases) or MDD (83 cases), as well as 101 healthy controls (HCs) between June 2018 and January 2022 were enrolled in this study. CD19+ B cells, CD3+ T cells, CD3–CD16/56+ NK cells, and total lymphocyte counts were strong predictors of the diagnosis of BD and MDD and were included in the differential diagnosis nomogram. The AUC of the nomogram and internal validation were 0.922 (95%; CI, 0.879–0.965), and 0.911 (95% CI, 0.838–0.844), respectively. The calibration curve used to discriminate BD from MDD showed optimal agreement between the nomogram and the actual diagnosis. The results of DCA showed that the net clinical benefit was significant.ConclusionThis is an easy-to-use, repeatable, and economical nomogram for differential diagnosis that can help clinicians in the individual diagnosis of BD and MDD patients, reduce the risk of misdiagnosis, facilitate the formulation of appropriate treatment strategies and intervention plans.</p

Presentation_1_Development and validation of a nomogram based on lymphocyte subsets to distinguish bipolar depression from major depressive disorder.ZIP

ObjectiveBipolar depression (BD) and major depressive disorder (MDD) are both common affective disorders. The common depression episodes make it difficult to distinguish between them, even for experienced clinicians. Failure to properly diagnose them in a timely manner leads to inappropriate treatment strategies. Therefore, it is important to distinguish between BD and MDD. The aim of this study was to develop and validate a nomogram model that distinguishes BD from MDD based on the characteristics of lymphocyte subsets.Materials and methodsA prospective cross-sectional study was performed. Blood samples were obtained from participants who met the inclusion criteria. The least absolute shrinkage and selection operator (LASSO) regression model was used for factor selection. A differential diagnosis nomogram for BD and MDD was developed using multivariable logistic regression and the area under the curve (AUC) with 95% confidence interval (CI) was calculated, as well as the internal validation using a bootstrap algorithm with 1,000 repetitions. Calibration curve and decision curve analysis (DCA) were used to evaluate the calibration and clinical utility of the nomogram, respectively.ResultsA total of 166 participants who were diagnosed with BD (83 cases) or MDD (83 cases), as well as 101 healthy controls (HCs) between June 2018 and January 2022 were enrolled in this study. CD19+ B cells, CD3+ T cells, CD3–CD16/56+ NK cells, and total lymphocyte counts were strong predictors of the diagnosis of BD and MDD and were included in the differential diagnosis nomogram. The AUC of the nomogram and internal validation were 0.922 (95%; CI, 0.879–0.965), and 0.911 (95% CI, 0.838–0.844), respectively. The calibration curve used to discriminate BD from MDD showed optimal agreement between the nomogram and the actual diagnosis. The results of DCA showed that the net clinical benefit was significant.ConclusionThis is an easy-to-use, repeatable, and economical nomogram for differential diagnosis that can help clinicians in the individual diagnosis of BD and MDD patients, reduce the risk of misdiagnosis, facilitate the formulation of appropriate treatment strategies and intervention plans.</p

Identification and Molecular Characterization of <i>FKF1</i> and <i>GI</i> Homologous Genes in Soybean

<div><p>In <i>Arabidopsis</i>, FKF1 (FLAVIN BINDING, KELCH REPEAT, F-BOX1) and GI (GIGANTEA) play important roles in flowering pathway through regulating daytime <i>CO</i> (<i>CONSTANS</i>) expression, and such a function is conserved across plants studied. But related reports are limited for soybean. In this study, we cloned <i>FKF1</i> and <i>GI</i> homologs in soybean, and named as <i>GmFKF1</i>, <i>GmFKF2</i>, <i>GmGI1</i>, <i>GmGI2</i>, and <i>GmGI3</i>, respectively. <i>GmGI1</i> had two alternative splicing forms, <i>GmGI1α</i> and <i>GmGI1β</i>. <i>GmFKF1</i>/<i>2</i> transcripts were diurnally regulated, with a peak at zeitgeber time 12 (ZT12) in long days and at ZT10 in short days. The diurnal phases between <i>GmGIs</i> transcript levels greatly differed. <i>GmGI2</i> expression was regulated by both the circadian clock and photoperiod. But the rhythmic phases of <i>GmGI1</i> and <i>GmGI3</i> expression levels were mainly conferred by long days. <i>GmFKFs</i> shared similar spatio-temporal expression profiles with <i>GmGIs</i> in all of the tissue/organs in different developmental stages in both LD and SD. Both GmFKF and GmGI proteins were targeted to the nucleus. Yeast two hybrid assays showed GmFKF1/GmFKF2 interacted with GmGI1/GmGI2/GmCDF1 (CYCLING DOF FACTOR CDF1 homolog in soybean); and the LOV (Light, Oxygen, or Voltage) domain in GmFKF1/GmFKF2 played an important role in these interactions. N-terminus of GmGI2 was sufficient to mediate its interaction with GmCDF1. Interestingly, N-terminus not full of GmGI3 interacted with GmFKF1/GmFKF2/GmCDF1. Ectopic over-expression of the <i>GmFKF1</i> or <i>GmFKF2</i> in <i>Arabidopsis</i> enhanced flowering in SD. Collectively, GmFKF and GmGI in soybean had conserved functional domains at DNA sequence level, but specific characters at function level with their homologs in other plants.</p></div

Data_Sheet_2_Development and validation of a nomogram based on lymphocyte subsets to distinguish bipolar depression from major depressive disorder.docx

ObjectiveBipolar depression (BD) and major depressive disorder (MDD) are both common affective disorders. The common depression episodes make it difficult to distinguish between them, even for experienced clinicians. Failure to properly diagnose them in a timely manner leads to inappropriate treatment strategies. Therefore, it is important to distinguish between BD and MDD. The aim of this study was to develop and validate a nomogram model that distinguishes BD from MDD based on the characteristics of lymphocyte subsets.Materials and methodsA prospective cross-sectional study was performed. Blood samples were obtained from participants who met the inclusion criteria. The least absolute shrinkage and selection operator (LASSO) regression model was used for factor selection. A differential diagnosis nomogram for BD and MDD was developed using multivariable logistic regression and the area under the curve (AUC) with 95% confidence interval (CI) was calculated, as well as the internal validation using a bootstrap algorithm with 1,000 repetitions. Calibration curve and decision curve analysis (DCA) were used to evaluate the calibration and clinical utility of the nomogram, respectively.ResultsA total of 166 participants who were diagnosed with BD (83 cases) or MDD (83 cases), as well as 101 healthy controls (HCs) between June 2018 and January 2022 were enrolled in this study. CD19+ B cells, CD3+ T cells, CD3–CD16/56+ NK cells, and total lymphocyte counts were strong predictors of the diagnosis of BD and MDD and were included in the differential diagnosis nomogram. The AUC of the nomogram and internal validation were 0.922 (95%; CI, 0.879–0.965), and 0.911 (95% CI, 0.838–0.844), respectively. The calibration curve used to discriminate BD from MDD showed optimal agreement between the nomogram and the actual diagnosis. The results of DCA showed that the net clinical benefit was significant.ConclusionThis is an easy-to-use, repeatable, and economical nomogram for differential diagnosis that can help clinicians in the individual diagnosis of BD and MDD patients, reduce the risk of misdiagnosis, facilitate the formulation of appropriate treatment strategies and intervention plans.</p

Data_Sheet_3_Development and validation of a nomogram based on lymphocyte subsets to distinguish bipolar depression from major depressive disorder.docx

ObjectiveBipolar depression (BD) and major depressive disorder (MDD) are both common affective disorders. The common depression episodes make it difficult to distinguish between them, even for experienced clinicians. Failure to properly diagnose them in a timely manner leads to inappropriate treatment strategies. Therefore, it is important to distinguish between BD and MDD. The aim of this study was to develop and validate a nomogram model that distinguishes BD from MDD based on the characteristics of lymphocyte subsets.Materials and methodsA prospective cross-sectional study was performed. Blood samples were obtained from participants who met the inclusion criteria. The least absolute shrinkage and selection operator (LASSO) regression model was used for factor selection. A differential diagnosis nomogram for BD and MDD was developed using multivariable logistic regression and the area under the curve (AUC) with 95% confidence interval (CI) was calculated, as well as the internal validation using a bootstrap algorithm with 1,000 repetitions. Calibration curve and decision curve analysis (DCA) were used to evaluate the calibration and clinical utility of the nomogram, respectively.ResultsA total of 166 participants who were diagnosed with BD (83 cases) or MDD (83 cases), as well as 101 healthy controls (HCs) between June 2018 and January 2022 were enrolled in this study. CD19+ B cells, CD3+ T cells, CD3–CD16/56+ NK cells, and total lymphocyte counts were strong predictors of the diagnosis of BD and MDD and were included in the differential diagnosis nomogram. The AUC of the nomogram and internal validation were 0.922 (95%; CI, 0.879–0.965), and 0.911 (95% CI, 0.838–0.844), respectively. The calibration curve used to discriminate BD from MDD showed optimal agreement between the nomogram and the actual diagnosis. The results of DCA showed that the net clinical benefit was significant.ConclusionThis is an easy-to-use, repeatable, and economical nomogram for differential diagnosis that can help clinicians in the individual diagnosis of BD and MDD patients, reduce the risk of misdiagnosis, facilitate the formulation of appropriate treatment strategies and intervention plans.</p