bluuebunny/crossref_metadata_2025 huggingface dataset:
Demographic Factors Influencing Adoption of Modern Technologies among Tomato Smallholder Farmers: A Case of Mboga Na Matunda Project in Iringa District
Authors: Mwaipungu Asheri , Philipo Frank , Nzali Agnes
Published: November 2023

Tomato (Solanum lycopersicum) is one the most useful vegetables in Africa and the world as it has contributed to income level of smallholder farmers. This study therefore assessed factors influencing the adoption of modern technologies among Tomato smallholder farmers in iringa District, Tanzania. The data were collected through interview, focus group discussion, and questionnaire from 60 respondents and analyzed by using SPSS version 20, and deductive approach method. The findings show that 83.3% of respondents were male. Age of the smallholder tomato producers, 21-40 were 70% active age group. The educational level of respondents are; primary education 51.7%, secondary education 33.3%, and post secondary education 15%. Household size 1-2 members is about 23.3%,3-4 members is 66.7%, and above 4 is 10% of respondents. The study confirm that, demographic factors including sex,age,education and household size influenced the decision making process of smallholder tomato producers of adopting technologies.
Educational Attainment and Lifetime Risk of Cardiovascular Disease
Authors: Magnani Jared W. , Ning Hongyan , Wilkins John T. , Lloyd-Jones Donald M. , Allen Norrina B.
Published: November 2023

Importance

Education is a social determinant of health. Quantifying its association with lifetime cardiovascular disease (CVD) risk has public health importance.

Objective

To calculate lifetime risk estimates of incident CVD and CVD subtypes and estimate years lived with and without CVD by education.

Design, Setting, and Participants

Included community-based cohort studies with adjudicated cardiovascular events used pooled individual-level data from 1985 to 2015 of 6 prospective cohort studies. The study team assessed the association between education and lifetime CVD risk with modified Kaplan-Meier and Cox models accounting for competing risk of noncardiovascular death. The study team estimated years lived with and without CVD by education with the Irwin restricted mean and the utility of adding educational attainment to CVD risk assessment. Participants (baseline 40 to 59 years old and 60 to 79 years old) were without CVD at baseline and had complete education, cardiovascular risk factors, and prospective CVD outcomes data. Data were analyzed from January 2022 to September 2022.

Exposures

Educational attainment (less than high school, high school completion, some college, or college graduate).

Main outcome and measures

Cardiovascular events (fatal and nonfatal coronary heart disease, heart failure, and stroke; CVD-related deaths; and total CVD encompassing any of these events).

Results

There were 40 998 participants (23 305 female [56.2%]) with a mean (SD) age of 58.1 (9.7) years for males and 58.3 (9.9) years for females. Compared with college graduates, those with less than high school or high school completion had higher lifetime CVD risks. Among middle-aged men, the competing hazard ratios (HRs) for a CVD event were 1.58 (95% CI, 1.38-1.80), 1.30 (95% CI, 1.10-1.46), and 1.16 (95% CI, 1.00-1.34) in those with less than high school, high school, and some college, respectively, compared with those with college completion. Among women, these competing HRs were 1.70 (95% CI, 1.49-1.95), 1.19 (95% CI, 1.05-1.35), and 0.98 (95% CI, 0.83-1.15). Individuals with higher education had longer duration of life prior to incident CVD. Education provided limited contribution toward enhancing CVD risk prediction.

Conclusions and relevance

Lower education was associated with lifetime CVD risk across adulthood; higher education translated to healthy longevity. Educational policy initiatives may associate with long-term health benefits.
Relationships of Work Productivity and Activity Impairment With Patient‐Reported Outcomes in Ankylosing Spondylitis: Results From Two Trials
Authors: Magrey Marina , Wei James Cheng‐Chung , Yndestad Arne , Bushmakin Andrew G. , Cappelleri Joseph C. , Dina Oluwaseyi , Deodhar Atul
Published: November 2023

Objective

We examined the relationships of work productivity and activity impairment with key patient‐reported outcomes (PROs) assessing pain, disease activity, and health‐related quality of life (HRQoL) in patients with ankylosing spondylitis (AS).

Methods

This post hoc analysis pooled available data from baseline to end of the double‐blind phase of phase 2 and 3 placebo‐controlled tofacitinib trials in patients with active AS. A repeated‐measures longitudinal model assessed the relationships (linear or nonlinear) between Work Productivity and Activity Impairment questionnaire in Spondyloarthritis (WPAI:SpA) domains (absenteeism, activity impairment, presenteeism, and productivity loss) as outcomes and key PROs (total back pain, nocturnal spinal pain, Patient Global Assessment of Disease Activity, AS Quality of Life, EuroQol 5‐Dimension 3‐Level [EQ‐5D‐3L], and EQ‐5D Visual Analog Scale [EQ‐5D‐VAS]) as predictors.

Results

Data from 330 to 475 patients were available, depending on the analysis. Relationships between WPAI:SpA domains and PROs were approximately linear. The worst PRO scores were associated with a decline in patients’ work capacity (measured by activity impairment, presenteeism, and productivity loss [>65%]); the best scores were associated with improvements in WPAI:SpA domains (8%–23%). Incremental PRO improvements were associated with improvement of activity impairment, presenteeism, and productivity loss. Relationships between absenteeism and PROs were the weakest, owing to absenteeism being low in the study population.

Conclusion

Evidence of linear relationships between work productivity and activity impairment with patient‐reported pain, disease activity, and HRQoL was observed. Interventions to control pain and disease activity and improve HRQoL are therefore likely to improve work productivity and reduce activity impairment in patients with AS.
The Home as an Infinite Screen
Authors: Tahan Lucia
Published: November 2023

The continuing digital tsunami is offering enhanced spatial opportunities for architects. The interaction of real space and virtual space can be choreographed along a spectrum that ranges from our mobile phone screens to full bodily immersion in digital reality. Architect Lucia Tahan exploits these possibilities in her design work using various methods of spatial computing. Here she takes us through some of her recent experiments and thoughts.
Touching, Licking, Tasting: Performing Multisensory Spatial Perception Through Extended‐Reality Models
Authors: Strunden Paula
Published: November 2023

There has been much written speculation about leaving the body on entering fully virtual space. However, it is clear that the only reason we can experience virtual reality is precisely because we are embodied. Transdisciplinary researcher and architectural artist Paula Strunden works at the intersection of the real and the virtual, exploiting our body's important conduits for complete sensory and visceral experience of augmented space.
Conjunctions Or, Space as Oxymoron
Authors: Pala Giacomo
Published: November 2023

Traditional architectural thought and practice decrees that buildings should be spatially homogeneous, revealing themselves to their viewers and users as episodic and carefully orchestrated wholes. Giacomo Pala argues that the world is more complex than this, and that the digital has further enhanced its heterogeneous festival of formal, semiotic and spatial jump‐cutting to establish conjunctions from which we can be architecturally inspired.
High‐Performance Infrared Photodetectors Driven by Interlayer Exciton in a Van Der Waals Epitaxy Grown HfS2/MoS2 Vertical Heterojunction
Authors: Son Minkyun , Jang Hanbyeol , Seo Dong‐Bum , Lee Ju Hyeok , Kim Jin , Kim Minsu , Kang Saewon , Yim Soonmin , Song Wooseok , Yoo Jung‐Woo , Kim Hyun You , Lee Sun Sook , An Ki‐Seok
Published: November 2023

The van der Waals (vdW) heterojunctions of transition metal dichalcogenides (TMDCs) provide an advanced platform for interlayer exciton generation to detect the exceeding cutoff wavelengths of individual TMDCs. Herein, the first demonstration of high‐performance infrared (IR) photodetectors driven by interlayer excitons and based on HfS2/MoS2 vdW heterojunctions grown by chemical vapor deposition is presented. HfS2 exhibits selective growth only on MoS2, establishing a vertical heterojunction that effectively generates interlayer excitons. The synthesized HfS2/MoS2 vertical heterojunction with type‐II band alignment exhibits a low interlayer bandgap and a significantly large interface area, enabling highly efficient IR detection. Moreover, the built‐in potential in HfS2/MoS2 plays a pivotal role in the outstanding photoresponse by suppressing the dark current and providing gradient band bending for the interlayer exciton‐induced photocarriers to drift toward each electrode. The HfS2/MoS2 photodetector exhibits remarkable performance, achieving a detectivity (D*) of ≈7 × 1013 Jones at 1550 nm, D* of ≈2 × 1014 Jones at 980 nm, and fast response time of 60 µs, surpassing previously reported 2D photodetectors. Overall, the successful demonstration of a photodetector based on vdW epitaxial HfS2/MoS2 paves the way for the advancement of large‐scale high‐performance IR sensors.
Phase‐Bridged Hierarchical Catalysts for Efficient and Stable Water Electrolysis
Authors: Zhang Yihan , Lee Sangjin , Jeong Seulgi , Son Eunbin , Baik Jeong Min , Han Young‐Kyu , Park Hyesung
Published: November 2023

The design and synthesis of low‐cost electrocatalysts with high catalytic activity and long‐term stability is a challenging task. This study utilizes a combination of electronic tuning and surface reconstruction to synthesize a ternary layered double hydroxide (LDH)/phosphide (P−NiCuFe−LDH) hierarchical‐structure catalyst that improves the kinetics of the hydrogen/oxygen evolution reactions in water electrolysis by facilitating the thermodynamically limited reaction pathways. Spectroscopic analyses indicate synergistic electronic interactions among the metal atoms in the LDH and phosphide layers via the P‐bridge effect. This cross‐layer interaction optimizes the electron transport pathways and reaction kinetics, enabling the proposed hierarchical electrocatalyst to exhibit high intrinsic activity. Theoretical calculations confirm the configuration of the cross‐phase bridges and elucidate the origin of the enhanced electrocatalytic effect of P−NiCuFe−LDH. For overall water splitting, the P−NiCuFe0.06−LDH || P−NiCuFe0.06−LDH system requires only 1.517 V to attain a current density of 10 mA cm−2. The P−O‐containing surface (generated in situ during water electrolysis) prevents metal‐ion leaching and endows P−NiCuFe−LDH with excellent operational stability; as demonstrated by the continuous long‐term stability test over 1000 h with negligible performance degradation. This study provides important insights into the design of rational hierarchical structures for a wide range of applications beyond water splitting.
High‐Sulfur Loading and Single Ion‐Selective Membranes for High‐Energy and Durable Decoupled Aqueous Batteries
Authors: Zhang Xinyuan , Zhang Bao , Yang Jin‐Lin , Wu Jiawen , Jiang Heng , Du Fei , Fan Hong Jin
Published: November 2023

The decoupled battery design is promising for breaking the energy density limit of traditional aqueous batteries. However, the complex battery configuration and low‐selective separator membranes restrict their energy output and service time. Herein, a zinc–sulfur decoupled aqueous battery is achieved by designing a high‐mass loading sulfur electrode and single ion‐selective membrane (ISM). A vertically assembled nanosheet network constructed with the assistance of a magnetic field enables facile electron and ion conduction in thick sulfur electrodes, which is conducive to boosting the cell‐level energy output. For the tailored ISM, the Na ions anchored on its skeleton effectively prevent the crossover of OH− or Cu2+, facilitating the transport of Na+ and ensuring structural and mechanical stability. Consequently, the Zn–S aqueous battery achieves a reversible energy density of 3988 Wh kgs−1 (by sulfur mass), stable operation over 300 cycles, and an energy density of 53.2 mWh cm−2. The sulfur‐based decoupled system may be of immediate benefit toward safe, reliable, and affordable static energy storage.
Boosting Alkaline Hydrogen Oxidation Activity of Ru Single‐Atom Through Promoting Hydroxyl Adsorption on Ru/WC1−x Interfaces
Authors: Park Jinkyu , Kim Honghui , Kim Seongbeen , Yi Seung Yeop , Min Hakyung , Choi Daeeun , Lee Seonggyu , Kim Jihan , Lee Jinwoo
Published: November 2023

The sluggish kinetics of the hydrogen oxidation reaction (HOR) in alkaline conditions continue to pose a significant challenge for the practical implementation of anion‐exchange membrane fuel cells. Developing single‐atom catalysts can accelerate the pace of new HOR catalyst discovery for highly cost‐effective and active HOR performance. However, single‐atom catalysts (SACs) for the alkaline HOR have rarely been reported, and fundamental studies on the rational design of SACs are still required. Herein, the design of Ru SAC supported on the tungsten carbide (Ru SA/WC1−x) via in situ high‐temperature annealing strategy is reported. The resulting Ru SA/WC1−x catalyst exhibits remarkably enhanced HOR performance in alkaline media, a level of activity that can not be achieved with carbon‐supported Ru SAC. Electrochemical results and density functional theory demonstrate that promoting the hydroxyl adsorption on Ru SA/WC1−x interfaces, which is derived from the low potential of zero charge of WC1–x support, has a significant effect on enhancing the HOR performance of SACs. This enhancement leads to 5.8 and 60.1 times higher Ru mass activity of Ru SA/WC1−x than Ru nanoparticles on carbon and Ru single‐atom on N‐doped carbon, respectively. This work provides new insights into the design of highly active SACs for alkaline HOR.
Convergence Analysis and Application for Multi‐Layer Neural Network Based on Fractional‐Order Gradient Descent Learning
Authors: Zhao Shuai , Fan Qinwei , Dong Qingmei
Published: November 2023

Fractional order calculus, with its inheritance and infinite memory properties, is a promising research area in information processing and modeling of certain physical systems, system identification, and control. In this paper, a fractional‐order gradient descent method is proposed for backpropagation training of multilayer feedforward neural networks. In particular, the Caputo derivative is used to define the measurement function and consider the smooth regular term. In addition, the monotonicity of the error function and the strong (weak) convergence theorem of the algorithm are rigorously proved. Finally, numerical experiments prove the correctness and effectiveness of the algorithm theory.
Phosphorous‐Doping Strategy Enabled “Concrete‐Slab”‐Like Zn Layer for Highly Stable 3D Composite Anode
Authors: Han Lei , Wang Qi , Pang Rui , Zhang Ding , Zhao Bo , Meng Weixue , Li Meng , Zhang Yingjiu , Cao Anyuan , Shang Yuanyuan
Published: November 2023

Zinc electroplating/stripping is a promising electrochemical reaction for aqueous battery anodes, offering advantages such as high safety, low cost, and fast reaction kinetics. However, the growth of zinc dendrites is a major obstacle impeding its commercialization. To address these challenges, a phosphorus‐doping strategy is proposed for preparing a high Zn‐affinity C3N4 coupled carbon nanotube 3D framework (PCN‐S). The addition of P facilitates the efficient crystallization of Zn that leads to the formation of a “concrete‐slab”‐like zinc layer on the PCN‐S surface. Moreover, the unique “release effect” possessed by the P‐doped 3D framework contributes to more stable cycling at high current. Such structural characteristics result in significantly enhanced stability of Zn metal deposition and extend the cycle life of full cells. The Zn@PCN‐S//Zn@PCN‐S symmetric cell exhibits an impressive long‐term cycle time exceeding 1500 h (1 mA cm‒2). Consequently, aqueous rechargeable zinc‐metal batteries constructed with the 3D Zn@PCN‐S anode can achieve a specific energy of approximately ≈340 mAh g‒1 and cycling for over 600 h. This work introduces a promising option for next‐generation energy storage technologies.
Spontaneous hierarchical surface engineering of minerals through coupled dissolution‐precipitation chemistry
Authors: Jiang Jinyang , Zhang Jiawen , Wang Lanxin , Lu Zeyu , Wang Fengjuan , Liu Zhiyong , Zeng Hongbo
Published: November 2023

Peculiar hierarchical microstructures in creatures inspire modern material design with distinct functionalities. Creatures can effortlessly construct sophisticated yet long‐range ordered microstructure across bio‐membrane through ion secretion and precipitation. However, microstructure biomimicry in current technology generally requires elaborate, point‐by‐point fabrication. Herein, a spontaneous yet controllable strategy is developed to achieve surface microstructure engineering through a natural surface phenomenon similar to ion secretion‐precipitation, that is, coupled dissolution‐precipitation. A series of hierarchical microstructures on mineral surfaces in fluids with tunable morphology, orientation, dimension, and spatial distribution are achieved by simply controlling initial dissolution and fluid chemistry. In seawater, long‐range ordered film of vertically aligned brucite flakes forms through interfacial dissolution, nucleation, and confinement‐induced orientation of flakes with vertically grown {110} plane, on the edge of which, fusiform aragonite epitaxially precipitates. With negligible initial surface dissolution, prismatic aragonite epitaxially grows on a calcite polyhedron‐packed surface. By tuning fluid chemistry, closely packed calcite polyhedron and loosely packed calcite micro‐pillars are engineered through rapid and retarded precipitation, respectively. Surprisingly, the spontaneously grown microstructures resemble those deliberately created by human or found in nature, and tremendously modulate surface functionality. These findings open new possibilities for facile and customizable engineering of microstructural surfaces, hierarchical heterostructures, and biomimetic materials.
Fast Antioxidation Kinetics of Glutathione Intracellularly Monitored by a Dual‐Wire Nanosensor
Authors: Jiao Yu‐Ting , Kang Yi‐Ran , Wen Ming‐Yong , Wu Hui‐Qian , Zhang Xin‐Wei , Huang Wei‐Hua
Published: November 2023

The glutathione (GSH) system is one of the most powerful intracellular antioxidant systems for the elimination of reactive oxygen species (ROS) and maintaining cellular redox homeostasis. However, the rapid kinetics information (at the millisecond to the second level) during the dynamic antioxidation process of the GSH system remains unclear. As such, we specifically developed a novel dual‐wire nanosensor (DWNS) that can selectively and synchronously measure the levels of GSH and ROS with high temporal resolution, and applied it to monitor the transient ROS generation as well as the rapid antioxidation process of the GSH system in individual cancer cells. These measurements revealed that the glutathione peroxidase (GPx) in the GSH system is rapidly initiated against ROS burst in a sub‐second time scale, but the elimination process is short‐lived, ending after a few seconds, while some ROS are still present in the cells. This study is expected to open new perspectives for understanding the GSH antioxidant system and studying some redox imbalance‐related physiological.
Photon Pair Source based on PPLN‐Waveguides for Entangled Two‐Photon Absorption
Authors: Gäbler Tobias Bernd , Hendra Patrick , Jain Nitish , Gräfe Markus
Published: November 2023

Fluorescence excitation by absorption of entangled photon pairs offers benefits compared to classical imaging techniques, such as the attainment of higher signal levels at low excitation power while simultaneously mitigating phototoxicity. However, current entangled photon pair sources are unreliable for fluorescence detection. In order to address this limitation, there is a need for ultra‐bright entangled photon pair sources. Among the potential solutions, sources utilizing nonlinear waveguides emerge as promising candidates to facilitate fluorescence excitation through entangled photons. In this paper, a source consisting of a periodically poled lithium niobate waveguide is developed and its key characteristics are analyzed. To demonstrate its suitability as key component for imaging experiments, the entangled two‐photon absorption behavior of Cadmium Selenide Zinc Sulfide quantum dot solutions is experimentally investigated.
The tryptophan catabolite or kynurenine pathway in autism spectrum disorder; a systematic review and meta‐analysis
Authors: Almulla Abbas F. , Thipakorn Yanin , Tunvirachaisakul Chavit , Maes Michael
Published: November 2023

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social communication and interaction, as well as rigid and unchanging interests and behaviors. Several studies have reported that activated immune‐inflammatory and nitro‐oxidative pathways are accompanied by depletion of plasma tryptophan (TRP), increased competing amino acid (CAAs) levels, and activation of the TRP catabolite (TRYCAT) pathway. This study aims to systematically review and meta‐analyze data on peripheral TRP, CAAs, TRYCAT pathway activity, and individual TRYCATs, including kynurenine (KYN) and kynurenic acid (KA) levels, in the blood and urine of ASD patients. After extensively searching PubMed, Google Scholar, and SciFinder, a total of 25 full‐text papers were included in the analysis, with a total of 6653 participants (3557 people with ASD and 3096 healthy controls). Our results indicate that blood TRP and the TRP/CAAs ratio were not significantly different between ASD patients and controls (standardized mean difference, SMD = −0.227, 95% confidence interval, CI: −0.540; 0.085, and SMD = 0.158, 95% CI: −0.042; 0.359), respectively. The KYN/TRP ratio showed no significant difference between ASD and controls (SMD = 0.001, 95% CI: −0.169; 0.171). Blood KYN and KA levels were not significantly changed in ASD. Moreover, there were no significant differences in urine TRP, KYN, and KA levels between ASD and controls. We could not establish increases in neurotoxic TRYCATs in ASD. In conclusion, this study demonstrates no abnormalities in peripheral blood TRP metabolism, indoleamine 2,3‐dioxygenase enzyme (IDO) activity, or TRYCAT production in ASD. Reduced TRP availability and elevated neurotoxic TRYCAT levels are not substantial contributors to ASD's pathophysiology.
Low cholesterol levels are associated with increasing risk of plasma cell neoplasm: A UK biobank cohort study
Authors: Li Linfeng , Yu Zhengyu , Ren Jianjun , Niu Ting
Published: November 2023

Background

Plasma cell neoplasms are a group of hematologic neoplasms that often develop in the elderly population. The relationship between cholesterol levels and hematologic malignancy has been identified in population studies. However, it is still unclear if there is a relationship between cholesterol levels and plasma cell neoplasm in European ancestry.

Methods

Prospective cohorts included 502,507 individuals from the UK Biobank who were followed up to 2019 and assessed total cholesterol(TC) levels, low‐density lipoprotein (LDL) levels, high‐density lipoprotein (HDL) levels, apolipoprotein A (ApoA) and apolipoprotein B (ApoB) as risk factors for plasma cell neoplasms with Cox proportional hazard regression and restricted cubic spline model. We also used two‐sample Mendelian randomization to determine if the cholesterol level has a causal effect on developing plasma cell neoplasms.

Results

We observed 1819 plasma cell neoplasm cases during 14.2 years of follow‐up in the UK Biobank. We found higher blood serum cholesterol levels at baseline were associated with a lower risk of plasma cell neoplasm in our study. All lipid profiles we analyzed in this study were inversely associated with plasma cell neoplasm risk (all ptrend <0.005) but triglycerides did not have such association. However, there was no suggestive association of genetically predicted serum LDL, HDL, and total cholesterol levels with multiple myeloma.

Conclusion

Low serum total cholesterol, LDL, HDL, ApoA, and ApoB levels were all associated with increasing the risk of plasma cell neoplasm.
Prognosis value of microscopic bile duct invasion in hepatocellular carcinoma: A multicenter study
Authors: Huang Qizhen , Lin Kongying , Lin Zhipeng , Ji Hongbin , Zhou Xiaoyu , Wang Bin , Chen Yufeng , Sun Chuandong , Zheng Shuguo , Chen Jinhong , Wang Yifan , Zhou Yanming , Zhou Weiping , Zeng Yongyi
Published: November 2023

Objective

To evaluate the prognostic significance of microscopic bile duct invasion (MiBDI) in hepatocellular carcinoma (HCC) following R0 resection.

Patients and Methods

Patients who underwent R0 resection for HCC at nine medical centers were stratified into five groups: neither bile duct nor vascular invasion (MiBDI−MVI−), microscopic bile duct invasion alone (MiBDI+MVI−), both microscopic bile duct and vascular invasion (MiBDI+MVI+), microscopic vascular invasion alone (MiBDI−MVI+), and macroscopic bile duct invasion (MaBDI). Overall survival (OS) was assessed using Kaplan–Meier analysis, and independent risk factors of OS were determined using Cox proportional hazards models.

Results

A total of 377 HCC cases were analyzed. The OS for MiBDI+MVI‐ was similar to that of MiBDI−MVI− (p > 0.05) but better than MiBDI+MVI+, MiBDI−MVI+, and MaBDI (all p < 0.05). Multivariate analysis indicated that MiBDI was not an independent risk factor for OS, while MVI and MaBDI were.

Conclusions

Overall survival (OS) in patients with MiBDI was superior to those with MVI and MaBDI. Isolated MiBDI did not influence OS in patients with HCC after R0 resection.
Kompetenz für Effizienz
Authors: Woppowa Ljuba
Published: November 2023

Im Fokus des 14. Jahrestreffens der Betriebsingenieure und Betriebsingenieurinnen der VDI‐Gesellschaft Verfahrenstechnik und Chemieingenieurwesen (VDI‐GVC) stehen die Themen Effizienz und Nachhaltigkeit. Mit ihren Kompetenzen leisten Betriebsingenieure entscheidende Beiträge dazu, Anlagen höchst effizient zu betreiben und Prozesse optimal zu fahren. Die Veranstaltung im November bietet die Möglichkeit zum direkten und persönlichen Austausch.
Unusual aliovalent Cd doped γ‐Bi2MoO6 nanomaterial for efficient photocatalytic degradation of sulfamethoxazole and rhodamine B under visible light irradiation
Authors: Zhang Bohang , Fang Canxiang , Ning Jing , Dai Rong , Liu Yang , Wu Qiao , Zhang Fuchun , Zhang Weibin , Dou Shixue , Liu Xinghui
Published: November 2023

Due to γ‐Bi2MoO6 (BMO) has attracted considerable attention because of its unique layered perovskite structure and excellent electrical conductivity. However, the easy recombination of electron–hole pairs limits its practical application. To address this issue, we successfully prepared aliovalent Cd2+ doped BMO (Cd‐BMO) by using a simple hydrothermal method for the degradation of the sulfamethoxazole (SMZ) and Rhodamine B (RhB). The result found that the degradation efficiency of Cd‐BMO is significantly higher than that of BMO, despite an increase in the bandgap after the introduction of Cd2+. The superior degradation efficiency of 8% Cd‐BMO, with a smaller particle size and larger specific surface area, can be attributed to its fast charge separation efficiency, low charge transfer resistance, and low rate of electron–hole pair recombination. Repeated and ion spillover experiments prove that 8% Cd‐BMO shows good stability and environmental protection. Theoretical simulation demonstrates that Cd offers electrons to the BMO system due to the decreased binding energy of BMO. The 8% Cd‐BMO sample can provide a suitable electric band edge for generating dominant active radicals during degradation. This work not only provides a potential candidate of 8% Cd‐BMO for practical degradation but also sheds light on the design of superior photocatalysts.
Relationships between plant species richness and grazing intensity in a semiarid ecosystem
Authors: Fulbright Timothy E. , Ortega‐Santos J. Alfonso , Hines Stacy L. , Drabek Dillan J. , Saenz Ramon , Campbell Tyler A. , Hewitt David G. , Wester David B.
Published: November 2023

Plant species richness is an important property of ecosystems that is altered by grazing. In a semiarid environment, we tested the hypotheses that (1) small‐scale herbaceous plant species richness declines linearly with increasing grazing intensity by large ungulates, (2) precipitation and percent sand interact with grazing intensity, and (3) response of herbaceous plant species richness to increasing intensity of ungulate grazing varies with patch productivity. During January–March 2012, we randomly allocated 50, 1.5‐m × 1.5‐m grazing exclosures within each of six 2500 ha study sites across South Texas, USA. We counted the number of herbaceous plant species and harvested vegetation in 0.25‐m2 plots within exclosures (ungrazed control plots) and in the grazed area outside the exclosures (grazed treatment plots) during October–November 2012–2019. We estimated percent use (grazing intensity) based on the difference in herbaceous plant standing crop between control plots and treatment plots. We selected the negative binomial regression model that best explained the relationship between grazing intensity and herbaceous plant species richness using the Schwarz‐Bayesian information criterion. After accounting for the positive effect of precipitation and percent sand on herbaceous plant species richness, species richness/0.25 m2 increased slightly from 0% to 30% grazing intensity and then declined with increasing grazing intensity. Linear and quadratic responses of herbaceous plant species richness to increasing grazing intensity were greater for the least productive patches (<15.7 g/0.25 m2) than for productive patches (≥15.7 g/0.25 m2). Our results followed the pattern predicted by the intermediate disturbance hypothesis model for the effect of grazing intensity on small‐scale herbaceous plant species richness.
Constructing indicator species distribution models to study the potential invasion risk of invasive plants: A case of the invasion of Parthenium hysterophorus in China
Authors: Liu Jiamin , Wei Haiyan , Zheng Jiaying , Chen Ruidun , Wang Lukun , Jiang Fan , Gu Wei
Published: November 2023

Aim

As invasive plants are often in a non‐equilibrium expansion state, traditional species distribution models (SDMs) are likely underestimating their suitable habitat. New methods are necessary to identify potential invasion risk areas.

Location

Tropical monsoon rainforest and subtropical evergreen broad‐leaved forest regions in China.

Methods

We took Parthenium hysterophorus as a case study to predict its potential invasion risk using climate, terrain, and human activity variables. First, a generalized joint attribute model (GJAM) was constructed using the occurrence of P. hysterophorus and its 27 closely related species in Taiwan, given it is widely distributed in Taiwan. Based on the output correlation values, two positively correlated species (Cardiospermum halicacabum and Portulaca oleracea) and one negatively correlated species (Crassocephalum crepidioides) were selected as indicator species. Second, the distributions of P. hysterophorus and its indicator species in the study area were predicted separately using an ensemble model (EM). Third, when selecting indicator species to construct indicator SDMs, two treatments (indicator species with positive correlation only, or both positive and negative correlation) were considered. The indicator species' EM predictions were overlaid using a weighted average method, and a better indicator SDMs prediction result was selected by comparison. Finally, the EM prediction result of P. hysterophorus was used to optimize the indicator SDMs result by a maximum overlay.

Results

The optimized indicator SDMs prediction showed an expanded range beyond the current geographic range compared to EM and the thresholds for predicting key environmental variables were wider. It also reinforced the human activities' influence on the potential distribution of P. hysterophorus.

Main Conclusions

For invasive plants with expanding ranges, information about indicator species distribution can be borrowed as a barometer for areas not currently invaded. The optimized indicator SDMs allow for more efficient potential invasion risk prediction. On this basis, invasive plants can be prevented earlier.
Seas the DNA? Limited detection of cetaceans by low‐volume environmental DNA transect surveys
Authors: Robinson Chloe V. , Migneault Amy , Dracott Karina , Glover Robin D.
Published: November 2023

Environmental DNA (eDNA) has begun to show promise as a robust and reproducible tool for monitoring cetaceans in coastal and offshore waters. Some limiting factors preventing the wider application of eDNA for cetacean monitoring includes lack of species‐specific qPCR assays and limited in situ validation. In this study, we determined 15 monitoring stations within cetacean hotspots in Chatham Sound (British Columbia, Canada), from which we collected a combination of visual and acoustic data, and low‐volume eDNA samples (equivalent to ~250 mL seawater). We designed novel eDNA assays for gray whale and Dall's porpoise and validated existing assays for harbor porpoise, killer whale, and humpback whale. Overall, we collected a total of 120 paired eDNA samples across four sampling intervals, 60 preserved with absolute ethanol and 60 preserved with propylene glycol antifreeze. Positive rates for visual (18%) and acoustic (4%) detections were higher than the eDNA detection rate (<3%), with only one sample (antifreeze‐preserved) producing a positive detection for humpback whales at one of the stations. We discuss factors which could have influenced the lack of detections and highlight the need for higher sample volumes and species‐specific sample approaches to improve detection success and confidence in eDNA applicability for cetacean monitoring.
Intelligent classification and analysis of regional landforms based on automatic feature selection
Authors: Xu Yuexue , Zhu Hongchun , Lu Zhiwei , Yang Yanrui , Zhu Guocan
Published: November 2023

Terrain features are an important basis for realizing high‐precision landform classification, and feature selection is a key step of machine learning and knowledge mining. However, the feature selection process is facing challenges due to the multidimensionality and correlation of multisource terrain feature datasets and factors. Traditional feature selection methods lack enough consideration for the interpretability and transparency of feature factors, but the transparent decision‐making process of feature selection precisely determines the modelling effect and the reliability of model application results. Current research urgently needs to work out the black holes of visual representation during feature selection. In the process of intelligent landform classification, multiple and effective terrain feature is an essential factor in enhancing the performance and generalisation ability of the network. Therefore, we initially selected 40 terrain feature parameters, including basic terrain factors and digital elevation model (DEM) terrain textures, to calculate the feature contribution degree and sort the parameter importance based on the SHapley Additive exPlanations (SHAP) method, then reserved 10%, 20%, 30%, 40% and 50% terrain features in turn for constructing the landform classification dataset. Because the traditional UNet network cannot completely capture abrupt landform features, the convolutional block attention module (CBAM) was integrated into the UNet, and a deep learning model was established for the fine‐grained classification of regional landforms. Considering the calculation rate, even though there are large regional spatial differences and genetic mechanisms, it is appropriate to retain 20% of terrain features for intelligent landform classification. The classification accuracy of typical regions, namely, the Hanzhong Basin, North China Plain, Yunnan–Guizhou Plateau and Tibetan Plateau, reached 98.76%, 97.36%, 96.3% and 92.78%, respectively, and what's more, some accuracies went up to a higher level under other feature combinations. Meanwhile, given the different feature combinations corresponding to regional landform types, the combinative stability and spatial orderliness characteristics were explored to explain the accuracy variation trend.
HK2 in microglia and macrophages contribute to the development of neuropathic pain
Authors: Wang Siyuan , Jiang Chao , Cao Kelei , Li Run , Gao Zhihua , Wang Yue
Published: November 2023

Neuropathic pain is a complex pain condition accompanied by prominent neuroinflammation involving activation of both central and peripheral immune cells. Metabolic switch to glycolysis is an important feature of activated immune cells. Hexokinase 2 (HK2), a key glycolytic enzyme enriched in microglia, has recently been shown important in regulating microglial functions. Whether and how HK2 is involved in neuropathic pain‐related neuroinflammation remains unknown. Using a HK2‐tdTomato reporter line, we found that HK2 was prominently elevated in spinal microglia. Pharmacological inhibition of HK2 effectively alleviated nerve injury‐induced acute mechanical pain. However, selective ablation of Hk2 in microglia reduced microgliosis in the spinal dorsal horn (SDH) with little analgesic effects. Further analyses showed that nerve injury also significantly induced HK2 expression in dorsal root ganglion (DRG) macrophages. Deletion of Hk2 in myeloid cells, including both DRG macrophages and spinal microglia, led to the alleviation of mechanical pain during the first week after injury, along with attenuated microgliosis in the ipsilateral SDH, macrophage proliferation in DRGs, and suppressed inflammatory responses in DRGs. These data suggest that HK2 plays an important role in regulating neuropathic pain‐related immune cell responses at acute phase and that HK2 contributes to neuropathic pain onset primarily through peripheral monocytes and DRG macrophages rather than spinal microglia.
Point‐of‐care detection of fibrosis in liver transplant surgery using near‐infrared spectroscopy and machine learning
Authors: Sharma Varun J. , Adegoke John A. , Fasulakis Michael , Green Alexander , Goh Su K. , Peng Xiuwen , Liu Yifan , Jackett Louise , Vago Angela , Poon Eric K. W. , Starkey Graham , Moshfegh Sarina , Muthya Ankita , D'Costa Rohit , James Fiona , Gordon Claire L. , Jones Robert , Afara Isaac O. , Wood Bayden R. , Raman Jaishankar
Published: November 2023

Introduction

Visual assessment and imaging of the donor liver are inaccurate in predicting fibrosis and remain surrogates for histopathology. We demonstrate that 3‐s scans using a handheld near‐infrared‐spectroscopy (NIRS) instrument can identify and quantify fibrosis in fresh human liver samples.

Methods

We undertook NIRS scans on 107 samples from 27 patients, 88 from 23 patients with liver disease, and 19 from four organ donors.

Results

Liver disease patients had a median immature fibrosis of 40% (interquartile range [IQR] 20–60) and mature fibrosis of 30% (10%–50%) on histopathology. The organ donor livers had a median fibrosis (both mature and immature) of 10% (IQR 5%–15%). Using machine learning, this study detected presence of cirrhosis and METAVIR grade of fibrosis with a classification accuracy of 96.3% and 97.2%, precision of 96.3% and 97.0%, recall of 96.3% and 97.2%, specificity of 95.4% and 98.0% and area under receiver operator curve of 0.977 and 0.999, respectively. Using partial‐least square regression machine learning, this study predicted the percentage of both immature (R2 = 0.842) and mature (R2 = 0.837) with a low margin of error (root mean square of error of 9.76% and 7.96%, respectively).

Conclusion

This study demonstrates that a point‐of‐care NIRS instrument can accurately detect, quantify and classify liver fibrosis using machine learning.
Exploring the link between drought‐related terms and public interests: Global insights from LSTM‐based predictions and Google Trends analysis
Authors: Shahabi‐Haghighi Seyed Mohammad Bagher , Hamidifar Hossein
Published: November 2023

Effective drought monitoring is of paramount importance in hydrology. It aids in mitigating the detrimental effects of water scarcity, facilitates sustainable resource management, and informs policy decisions. Therefore, it is crucial to comprehensively comprehend the dynamics and trends of drought‐related phenomena. This study aims to explore the relationship between six low water quantity terms including drought, water crisis, water scarcity, water shortage, water stress, and water insecurity and some socio‐economic, geographic, and demographic parameters for different regions of the world and to predict the future trend of public interest in the mentioned terms using Long Short‐Term Memory neural network (LSTM) models. Google Trend data analysis was used to examine the public interest in these terms from 2017 to 2022. The LSTM models were trained using historical data on the studied terms, and their performance was evaluated using Root Mean Square Error (RMSE) indicator. The Google Trend data analysis showed that public interest in water shortage and water insecurity increased significantly from 2017 to 2022. The LSTM models showed promising results for predicting future trends in the mentioned water related issues, with RMSE scores (dimensionless) ranging from 0.04 to 0.43. The most significant socio‐economic, geographic and demographic parameters were found to be population, life expectancy, access to drinking water, and access to Internet while there was no correlation between precipitation and searched terms. The results suggest that LSTM models can be an effective tool for forecasting water related issues and emphasizes the importance of socio‐economic, geographic and demographic parameters in the public search behaviour around the world. The study also highlights the increasing public awareness of water related issues and the need for sustainable water management practices, particularly in regions with high water shortage and insecurity. The LSTM‐based prediction models in this study have practical applications in early warning systems for droughts, community education on water conservation, prioritizing vulnerable areas, assessing public perception of climate change's relation to droughts, and evaluating water policies. Further research is needed to improve the accuracy of these models incorporating the effective parameters and to develop effective strategies for managing water resources in regions facing water scarcity.
Effect of stretching on inflammation in a subcutaneous carrageenan mouse model analyzed at single‐cell resolution
Authors: Berrueta Lisbeth , Muñoz‐Vergara Dennis , Martin Daniel , Thompson Rebecca , Sansbury Brian E. , Spite Matthew , Badger Gary J. , Langevin Helene M.
Published: November 2023

Understanding the factors that influence the biological response to inflammation is crucial, due to its involvement in physiological and pathological processes, including tissue repair/healing, cancer, infections, and autoimmune diseases. We have previously demonstrated that in vivo stretching can reduce inflammation and increase local pro‐resolving lipid mediators in rats, suggesting a direct mechanical effect on inflammation resolution. Here we aimed to explore further the effects of stretching at the cellular/molecular level in a mouse subcutaneous carrageenan‐inflammation model. Stretching for 10 min twice a day reduced inflammation, increased the production of pro‐resolving mediator pathway intermediate 17‐HDHA at 48 h postcarrageenan injection, and decreased both pro‐resolving and pro‐inflammatory mediators (e.g., PGE2 and PGD2) at 96 h. Single‐cell RNA sequencing analysis of inflammatory lesions at 96 h showed that stretching increased the expression of both pro‐inflammatory (Nos2) and pro‐resolution (Arg1) genes in M1 and M2 macrophages at 96 h. An intercellular communication analysis predicted specific ligand–receptor interactions orchestrated by neutrophils and M2a macrophages, suggesting a continuous neutrophil presence recruiting immune cells such as activated macrophages to contain the antigen while promoting resolution and preserving tissue homeostasis.
Physiologically Based Pharmacokinetic Modeling of Nilotinib for Drug‐Drug Interactions, Pediatric Patients, and Pregnancy and Lactation
Authors: Liu Xiaomei I. , Leong Ruby , Burckart Gilbert J. , Dallmann André
Published: November 2023

Nilotinib is a second‐generation BCR‐ABL tyrosine kinase inhibitor for the treatment of Philadelphia chromosome‐positive chronic myeloid leukemia in both adult and pediatric patients. The pharmacokinetics (PK) of nilotinib in specific populations such as pregnant and lactating people remain poorly understood. Therefore, the objectives of the current study were to develop a physiologically based pharmacokinetic (PBPK) model to predict nilotinib PK in virtual drug‐drug interaction (DDI) studies, as well as in pediatric, pregnant, and lactating populations. The nilotinib PBPK model was built in PK‐Sim, which is part of the free and open‐source software Open Systems Pharmacology. The observed clinical data for the validation of the nilotinib models were obtained from the literature. The model reasonably predicted nilotinib concentrations in the adult population; the DDIs between nilotinib and rifampin or ketoconazole in the adult population; and the PK in the pediatric, pregnant, and lactating populations, although in the latter 2 populations plasma concentrations were slightly underestimated. The ratio of predicted versus observed PK parameters for the adult model ranged from 0.71 to 1.11 for area under the concentration‐time curve and 0.55 to 0.95 for maximum concentration. For the DDI, the predicted area under the concentration‐time curve ratio and maximum concentration ratio fell within the Guest criterion. The current study demonstrated the utility of using PBPK modeling to understand the mechanistic basis of PK differences between adults and specific populations, such as pediatrics, and pregnant and lactating individuals, indicating that this technology can potentially inform or optimize dosing conditions in specific populations.