bluuebunny/crossref_metadata_2025 huggingface dataset:
Multifaceted roles of IKZF1 gene, perspectives from bench to bedside
Authors: Feng Lin , Zhang Hang , Liu Ting
Published: June 2024

The IKZF1 gene encodes a transcription factor that belongs to the family of zinc-finger DNA-binding proteins associated with chromatin remodeling. The protein product, IKAROS, had been proved to regulate lymphopoiesis. Subsequent mouse model studies have further confirmed its regulating role in lymphopoiesis as well as in hematopoiesis; besides, it associates with immune function, certain immune disorders like common variable immunodeficiency and dysgammaglobulinemia have been proved to be associated with germline IKZF1 mutations. Dysfunction of IKAROS also bears paramount significance in leukemic transformation and alterations of IKZF1 gene predicts a poor prognosis in hematological malignancies. As an independent prognostic marker, IKZF1 has been incorporated in the risk stratification of BCP-ALL and stratification-guided therapy has also been generated. In this review, we provide a concise and comprehensive overview on the multifaceted roles of IKZF1 gene.
Real-world evaluation of health-related quality of life in patients with diffuse large B-cell lymphoma based on a multinational survey
Authors: Johnson P. Connor , Bailey Abigail , Ma Qiufei , Milloy Neil , Butcher Jake , Sanderson Isaac , Weatherby Sarah , Meadows Rachael , Quek Ruben G. W.
Published: June 2024

Background

Real-world health-related quality of life (HRQoL) data in patients with diffuse large B-cell lymphoma (DLBCL) are scarce. This study is to compare patient-reported outcomes in patients with DLBCL across therapy lines and countries.

Methods

Data were derived from the Adelphi DLBCL Disease Specific Programme™ from January 2021 to May 2021, a survey of physicians and their DLBCL patients in France, Germany, Italy, Spain, United Kingdom (UK), and the United States (US).

Results

Overall, analysis was conducted on 441 patients with DLBCL across Europe and the US (mean age 64.6 years, 64% male); 68% had an Ann Arbor stage III and 69% had an Eastern Cooperative Oncology Group Performance Status of 0 to 1. The mean overall GHS/QoL was 54.1; patients on their 3L+ therapy had a lower mean GHS/QoL compared with patients on 1L/2L (P = 0.0033). Further to this, mean EQ-5D-5L utility score was reduced from 0.73 for patients on 1L therapy to 0.66 for patients on 3L+ therapies (P = 0.0149). Mean percentages of impairment while working and overall work impairment were lower for patients receiving 3L+ therapy (12.5% and 17.7%; respectively) than those on 1L therapy (35.6% and 33.8%; respectively). When comparing region, patients in the US had significantly better scores for all functioning and symptomatic scales (per EORTC QLQ-C30) and work impairment (per WPAI) vs. patients with DLBCL in Europe. WPAI scores indicate that the overall activity impairment in the US was 36.6% and in Europe ranged from 42.4% in the UK to 54.9% in Germany. Mean EQ-5D-5L utility score for the US was 0.80, compared to 0.60 – 0.80 across the countries in Europe. Regression analysis showed patients who relapsed after more than one year of treatment were associated with better patient reported outcomes than those who relapse after less than one year.

Conclusion

Patient-reported outcomes of DLBCL patients remain poor and patients continue to experience considerable morbidity.
Assessment of KRASG12C inhibitors for colorectal cancer
Authors: Piazza Gary A. , Chandrasekaran Preethi , Maxuitenko Yulia Y. , Budhwani Karim I.
Published: June 2024

Colorectal cancer (CRC) is a highly prevalent and lethal cancer worldwide. Approximately 45% of CRC patients harbor a gain-in-function mutation in KRAS. KRAS is the most frequently mutated oncogene accounting for approximately 25% of all human cancers. Gene mutations in KRAS cause constitutive activation of the KRAS protein and MAPK/AKT signaling, resulting in unregulated proliferation and survival of cancer cells and other aspects of malignant transformation, progression, and metastasis. While KRAS has long been considered undruggable, the FDA recently approved two direct acting KRAS inhibitors, Sotorasib and Adagrasib, that covalently bind and inactivate KRASG12C. Both drugs showed efficacy for patients with non-small cell lung cancer (NSCLC) diagnosed with a KRASG12C mutation, but for reasons not well understood, were considerably less efficacious for CRC patients diagnosed with the same mutation. Thus, it is imperative to understand the basis for resistance to KRASG12C inhibitors, which will likely be the same limitations for other mutant specific KRAS inhibitors in development. This review provides an update on clinical trials involving CRC patients treated with KRASG12C inhibitors as a monotherapy or combined with other drugs. Mechanisms that contribute to resistance to KRASG12C inhibitors and the development of novel RAS inhibitors with potential to escape such mechanisms of resistance are also discussed.
Pulmonary haemorrhage and haemoptysis associated with bevacizumab-related treatment regimens: a retrospective, pharmacovigilance study using the FAERS database
Authors: Hu Huiping , Fu Zhiwen , Liu Jinmei , Zhang Cong , Li Shijun , Zhang Yu , You Ruxu
Published: June 2024

Background: Bevacizumab (BV) is widely used in routine cancer treatment and clinical therapy in combination with many other agents. This study aims to describe and analyse post-market cases of pulmonary haemorrhage and haemoptysis reported with different BV treatment regimens by mining data from the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database.

Methods: Data were collected from the FAERS database between 2004 Q1 and 2023 Q1. Disproportionality analysis including the reporting odds ratio (ROR) was employed to quantify the signals of disproportionate reporting of pulmonary haemorrhage and haemoptysis adverse events (AEs) associated with BV-related treatment regimens. The demographic characteristics, time to onset and outcomes were further clarified.

Results: A total of 55,184 BV-associated reports were extracted from the FAERS database, of which 497 reports related to pulmonary haemorrhage and haemoptysis. Overall, the median onset time of pulmonary haemorrhage and haemoptysis AEs was 43 days (interquartile range (IQR) 15-117 days). In the subgroup analysis, BV plus targeted therapy had the longest median onset time of 90.5 days (IQR 34-178.5 days), while BV plus chemotherapy had the shortest of 40.5 days (IQR 14–90.25). BV plus chemotherapy disproportionately reported the highest percentage of death (148 deaths out of 292 cases, 50.68%). Moreover, the BV-related treatments including four subgroups in our study demonstrated the positive signals with the association of disproportionate reporting of pulmonary haemorrhage and haemoptysis. Notably, BV plus chemotherapy showed a significant higher reporting risk in pulmonary haemorrhage and haemoptysis signals of disproportionate reporting in comparison to BV monotherapy (ROR 5.35 [95% CI, 4.78–6.02] vs. ROR 4.19 [95% CI, 3.56–4.91], p = 0.0147).

Conclusion: This study characterized the reporting of pulmonary haemorrhage and haemoptysis, along with the time to onset and demographic characteristics among different BV-related treatment options. It could provide valuable evidence for further studies and clinical practice of BV.
Effects of nitrogen addition and Bothriochloa ischaemum and Lespedeza davurica mixture on plant chlorophyll fluorescence and community production in semi-arid grassland
Authors: Wang Fugang , Shi Lei , Zhang Ruiyi , Xu Weizhou , Bo Yaojun
Published: June 2024

Background

Grass-legume mixture can effectively improve productivity and stimulate overyielding in artificial grasslands, but may be N-limited in semi-arid regions. This study investigated the effects of N addition on chlorophyll fluorescence and production in the grass-legume mixtures community.

Methods

An N addition experiment was conducted in the Bothriochloa ischaemum and Lespedeza davurica mixture community, with seven mixture ratios (B0L10, B2L8, B4L6, B5L5, B6L4, B8L2, and B10L0) according to the sowing abundance of B.ischaemum and L.davurica and four N addition levels, N0, N25, N50, and N75 (0,25,50,75kgNhm-2 a-1), respectively. We analyzed the response of chlorophyll fluorescence parameters of the two species, the rapid light-response curves of chlorophyll fluorescence, as well as aboveground biomass (AGB) and overyielding.

Results

Our results showed that the two species showed different photosynthetic strategies, with L.davurica having significantly higher initial fluorescence (Fo), effective photochemical quantum yield of PSII (ΦPSII), and coefficient of photochemical fluorescence quenching (qP) than B. ischaemum, consisting with results of rapid light-response curves. N addition and mixture ratio both had significant effects on chlorophyll fluorescence and AGB (p<0.001). The ΦPSII and qP of L.davurica were significantly lowest in B5L5 and B6L4 under N addition, and the effect of N varied with mixture ratio. The photosynthetic efficiency of B. ischaemum was higher in mixture than in monoculture (B10L0), and ΦPSII was significantly higher in N50 than in N25 and N50 at mixture communities except at B5L5. The community AGB was significantly higher in mixture communities than in two monocultures and highest at B6L4. In the same mixture ratio, the AGB was highest under the N50. The overyielding effects were significantly highest under the N75 and B6L4 treatments, mainly attributed to L.davurica. The partial least squares path models demonstrated that adding N increased soil nutrient content, and complementary utilization by B.ischaemum and L.davurica increased the photosynthetic efficiency. However, as the different photosynthetic strategies of these two species, the effect on AGB was offset, and the mixture ratio’s effects were larger than N. Our results proposed the B6L4 and N50 treatments were the optimal combination, with the highest AGB and overyielding, moderate grass-legume ratio, optimal community structure, and forage values.
Nonsuicidal self-injury among Chinese university students during the post-COVID-19 era: analysis of sex differences and the impact of gender role conflict
Authors: Xin Moye , Petrovic Julia , Yang Chengxi , Zhang Lijin , Yang Xueyan
Published: June 2024

Background

Global centers of epidemic prevention and control have entered a new stage of normalization, namely, the “post-COVID-19 era.” During the post-COVID-19 era, which is characterized by the time period following that with the most serious medical consequences, the psychosocial consequences of the COVID-19 pandemic began to receive worldwide attention, especially the degree of psychological distress it caused.

Aim

This study explored the differential impact of gender role conflict on Chinese university students’ engagement in nonsuicidal self-injury (NSSI) as a function of biological sex following the global COVID-19 pandemic.

Methods

Participants were 1,600 university students in northwestern China (Mage = 21.3 years; 50.8% women) who completed online measures of demographic variables (including biological sex, gender role conflict, and NSSI engagement).

Results

Women reported significantly more gender role conflicts than men did, while engagement in NSSI was significantly more prevalent among men than women. A total of 262 men reported engaging in at least one NSSI behavior, resulting in a prevalence rate of 33.25%. In comparison, a total of 106 individuals reported engaging in at least one NSSI behavior, resulting in a prevalence rate of 13.05% among women. Gender role conflict was found to significantly predict university students’ NSSI engagement, regardless of biological sex.

Conclusion

This is the first empirical study to identify sex differences in both gender role conflict and engagement in NSSI among university students in Northwestern China during the post-COVID-19 era. In addition, the present study is the first to demonstrate how gender role conflict predicts engagement in NSSI across sexes. These findings will inform the literature on gender role conflict and NSSI, particularly the close relationship between gender role conflict and engagement in NSSI among Chinese university students, and they emphasize the need for continued efforts to explore NSSI cross-culturally.
Caring for people with disability and human growth: evolutionary perspectives and contribution to psychological wellbeing
Authors: Bernacer Javier
Published: June 2024

From an evolutionary point of view, organisms with mutations resulting in maladaptation are an unavoidable result of genetic variability, and they do not usually survive natural selection. Thus, they do not produce benefits for the species. I contend that this is different in humans at two levels. First, the existence of people with disability has been essential for human growth as a species. Human ancestors' evolving cognitive and social abilities were boosted by caring for vulnerable members of the species, including premature offspring and people with disability. Therefore, caregiving was an essential trait of the evolution of humans, intertwined with the development of bipedalism, the hand, face, vocal apparatus, and brain. Second, caring for disability is also a source of growth at a personal level. Even though most scientific literature focuses on the stress and burden caused by caring for people with disability, there is solid evidence to accept caregiving as a source of happiness and flourishing for human beings. Hence, disability still has an essential role in improving human life nowadays. Contrary to this evidence, influential utilitarian bioethicists promote the elimination of disability from modern societies. Following the arguments presented here, this will lead to the withering of society. In conclusion, disability should be acknowledged as an essential source of growth for the human species.
Serine racemase deletion alters adolescent social behavior and whole-brain cFos activation
Authors: Brown Stephanie E. , Wang Ziyi (Zephyr) , Newman Emily L. , Engin Elif , Berretta Sabina , Balu Darrick T. , Folorunso Oluwarotimi O.
Published: June 2024

Background

Neurodevelopmental disorders (NDDs) can cause debilitating impairments in social cognition and aberrant functional connectivity in large-scale brain networks, leading to social isolation and diminished everyday functioning. To facilitate the treatment of social impairments, animal models of NDDs that link N- methyl-D-aspartate receptor (NMDAR) hypofunction to social deficits in adulthood have been used. However, understanding the etiology of social impairments in NDDs requires investigating social changes during sensitive windows during development.

Methods

We examine social behavior during adolescence using a translational mouse model of NMDAR hypofunction (SR-/-) caused by knocking out serine racemase (SR), the enzyme needed to make D-serine, a key NMDAR coagonist. Species-typical social interactions are maintained through brain-wide neural activation patterns; therefore, we employed whole-brain cFos activity mapping to examine network-level connectivity changes caused by SR deletion.

Results

In adolescent SR-/- mice, we observed disinhibited social behavior toward a novel conspecific and rapid social habituation toward familiar social partners. SR-/- mice also spent more time in the open arm of the elevated plus maze which classically points to an anxiolytic behavioral phenotype. These behavioral findings point to a generalized reduction in anxiety-like behavior in both social and non-social contexts in SR-/- mice; importantly, these findings were not associated with diminished working memory. Inter-regional patterns of cFos activation revealed greater connectivity and network density in SR-/- mice compared to controls.

Discussion

These results suggest that NMDAR hypofunction – a potential biomarker for NDDs – can lead to generalized behavioral disinhibition in adolescence, potentially arising from disrupted communication between and within salience and default mode networks.
Enhancing Alzheimer’s disease diagnosis and staging: a multistage CNN framework using MRI
Authors: Ali Muhammad Umair , Kim Kwang Su , Khalid Majdi , Farrash Majed , Zafar Amad , Lee Seung Won
Published: June 2024

This study addresses the pervasive and debilitating impact of Alzheimer’s disease (AD) on individuals and society, emphasizing the crucial need for timely diagnosis. We present a multistage convolutional neural network (CNN)-based framework for AD detection and sub-classification using brain magnetic resonance imaging (MRI). After preprocessing, a 26-layer CNN model was designed to differentiate between healthy individuals and patients with dementia. After detecting dementia, the 26-layer CNN model was reutilized using the concept of transfer learning to further subclassify dementia into mild, moderate, and severe dementia. Leveraging the frozen weights of the developed CNN on correlated medical images facilitated the transfer learning process for sub-classifying dementia classes. An online AD dataset is used to verify the performance of the proposed multistage CNN-based framework. The proposed approach yielded a noteworthy accuracy of 98.24% in identifying dementia classes, whereas it achieved 99.70% accuracy in dementia subclassification. Another dataset was used to further validate the proposed framework, resulting in 100% performance. Comparative evaluations against pre-trained models and the current literature were also conducted, highlighting the usefulness and superiority of the proposed framework and presenting it as a robust and effective AD detection and subclassification method.
Baseline monocyte count predicts symptom improvement during intravenous ketamine therapy in treatment-resistant depression: a single-arm open-label observational study
Authors: Pedraz-Petrozzi Bruno , Spangemacher Moritz , Deicher Anton , Drews Lena , Defert Julie , Silva-Colmenero Ana Yaiza , Wein Paul , Riedinger Elena , Gründer Gerhard , Gilles Maria , Sartorius Alexander , Reinwald Jonathan R.
Published: June 2024

Background

Neuroinflammatory processes in depression are associated with treatment resistance to conventional antidepressants. Ketamine is an effective new therapeutic option for treatment-resistant depression (TRD). Its well-established immunomodulatory properties are hypothesized to mediate its antidepressant effect. In this context, higher levels of inflammation may predict a better treatment response. However, conclusive evidence for this hypothesis is lacking. We thus investigated whether standard peripheral inflammatory cell markers and C-reactive protein (CRP) levels could predict symptom improvement during intravenous ketamine therapy in TRD patients.

Methods

27 participants with TRD were treated with six weight-adjusted intravenous ketamine infusions (0.5 mg/kg bodyweight) over three weeks. Baseline assessments included CRP, absolute monocyte count (AMC), and absolute neutrophil count (ANC). Depression severity was measured using the Montgomery-Åsberg Depression Rating Scale (MADRS) at baseline (D1), after the first (D3) and before the last ketamine infusion (D18). Raters were blinded for the baseline laboratory assessments.

Results

13 participants responded to ketamine treatment, and 8 participants partially responded. Baseline AMC showed a strong negative correlation with MADRS change at D3 (r=-0.57, p=0.002) and at D18 (r =-0.48, p=0.010), indicating that a high baseline AMC was associated with greater symptom improvement. A generalized linear model confirmed the association of baseline AMC with symptom improvement during ketamine treatment when additionally accounting for age, sex, and body mass index. Specifically, baseline AMC demonstrated predictive value to discriminate responders and partial responders from non-responders, but lacked discriminative ability between partial responders and responders. Baseline ANC correlated with the MADRS changes at D3 (r=-0.39, p=0.046), while CRP values did not correlate at all.

Conclusions

Our prospective single-arm open-label observational study demonstrated that baseline AMC reliably predicted symptom improvement during intravenous ketamine treatment in TRD patients. AMC could therefore serve as a simple and easily accessible marker for symptom improvement during ketamine therapy in daily clinical practice. Future studies with larger sample sizes and a more detailed longitudinal assessment of AMC subtypes are needed to better understand the specific relationship between monocytes and the neuromodulatory effects of ketamine.
Genomic modifications for enhanced antibiotic production in rifamycin derivative-producing Amycolatopsis mediterranei S699 strains: focusing on rifQ and rifO genes
Authors: Müller Moritz , Bialas Elena , Sturm Irina , Sood Utkarsh , Lal Rup , Bechthold Andreas
Published: June 2024

Rifamycin and its derivatives are natural products that belong to the class of antibiotic-active polyketides and have significant therapeutic relevance within the therapy scheme of tuberculosis, a worldwide infectious disease caused by Mycobacterium tuberculosis. Improving the oral bioavailability of rifamycin B was achieved through semisynthetic modifications, leading to clinically effective derivatives such as rifampicin. Genetic manipulation of the rifamycin polyketide synthase gene cluster responsible for the production of rifamycin B in the Amycolatopsis mediterranei strain S699 represents a promising tool to generate new rifamycins. These new rifamycins have the potential to be further derivatized into new, ideally more effective, clinically usable compounds. However, the resulting genetically engineered strains only produce these new derivatives in low yields. One example is the strain DCO36, in which rifAT6 was replaced by rapAT2, resulting in the production of rifamycin B and the new derivative 24-desmethyl rifamycin B. Here we describe the successful method adaptation of the PCR-targeting Streptomyces gene replacement approach to Amycolatopsis mediterranei S699 and further on the implementation of genetic modifications that enable an increased production of the derivative 24-desmethyl rifamycin B in the mutant strain DCO36. The described genetic modifications resulted in a mutant strain of DCO36 with rifQ deletion showing a 62% increase in 24-desmethyl rifamycin B production, while a mutant with rifO overexpression showed a 27% increase.
Plant leaf disease recognition based on improved SinGAN and improved ResNet34
Authors: Chen Jiaojiao , Hu Haiyang , Yang Jianping
Published: June 2024

The identification of plant leaf diseases is crucial in precision agriculture, playing a pivotal role in advancing the modernization of agriculture. Timely detection and diagnosis of leaf diseases for preventive measures significantly contribute to enhancing both the quantity and quality of agricultural products, thereby fostering the in-depth development of precision agriculture. However, despite the rapid development of research on plant leaf disease identification, it still faces challenges such as insufficient agricultural datasets and the problem of deep learning-based disease identification models having numerous training parameters and insufficient accuracy. This paper proposes a plant leaf disease identification method based on improved SinGAN and improved ResNet34 to address the aforementioned issues. Firstly, an improved SinGAN called Reconstruction-Based Single Image Generation Network (ReSinGN) is proposed for image enhancement. This network accelerates model training speed by using an autoencoder to replace the GAN in the SinGAN and incorporates a Convolutional Block Attention Module (CBAM) into the autoencoder to more accurately capture important features and structural information in the images. Random pixel Shuffling are introduced in ReSinGN to enable the model to learn richer data representations, further enhancing the quality of generated images. Secondly, an improved ResNet34 is proposed for plant leaf disease identification. This involves adding CBAM modules to the ResNet34 to alleviate the limitations of parameter sharing, replacing the ReLU activation function with LeakyReLU activation function to address the problem of neuron death, and utilizing transfer learning-based training methods to accelerate network training speed. This paper takes tomato leaf diseases as the experimental subject, and the experimental results demonstrate that: (1) ReSinGN generates high-quality images at least 44.6 times faster in training speed compared to SinGAN. (2) The Tenengrad score of images generated by the ReSinGN model is 67.3, which is improved by 30.2 compared to the SinGAN, resulting in clearer images. (3) ReSinGN model with random pixel Shuffling outperforms SinGAN in both image clarity and distortion, achieving the optimal balance between image clarity and distortion. (4) The improved ResNet34 achieved an average recognition accuracy, recognition precision, recognition accuracy (redundant as it’s similar to precision), recall, and F1 score of 98.57, 96.57, 98.68, 97.7, and 98.17%, respectively, for tomato leaf disease identification. Compared to the original ResNet34, this represents enhancements of 3.65, 4.66, 0.88, 4.1, and 2.47%, respectively.
Characteristic times for radiation belt drift phase mixing
Authors: Lejosne Solène , Albert Jay M. , Ratliff Daniel
Published: June 2024

Impulsive radial transport events occurring in the radiation belts leave lasting marks in the form of drift echoes, that is, energy-dependent drift phase structures in the radiation belts that evolve at the drift frequency. Drift echoes are known to be transient structures that dissipate due to phase mixing. The objective of this paper is to discuss how much time it takes for drift echoes to dissipate, and what drives this phase-mixing process. While any uncertainty or perturbation in the variables controlling trapped particles’ drift frequency contributes to phase mixing, we highlight two main drivers: the observational uncertainty associated with the finite size of the instrument energy channels, and the natural field fluctuations driving perturbations in trapped particles’ drift frequency. It is the combination of both instrumental and natural sources of phase mixing that determines the observed dissipation and lifetime of drift echoes. This means that the observed magnitude and lifetime of a drift echo are always underestimations of the natural magnitude and lifetime of the structure. This calls into question the applicability of the standard, drift-averaged formulation of radial diffusion. The three key points of the study are the following: First, the time it takes for particles initially localized in local time to phase-mix is measured in hours in the Earth’s radiation belts. Second, phase mixing at the drift scale is primarily due to uncertainties in measured kinetic energy and field perturbations. Third, our analysis can be utilized to set an energy resolution requirement for future particle instruments.
Optimizing animal care through compound feed management in Saudi Arabia
Authors: Alnafissa Mohamad , Alotaibi Bader Alhafi , Aldawdahi Nageeb , Imran Azeem Muhammad , Muddassir Muhammad
Published: June 2024

Proper animal feeding practices play a fundamental role in enhancing livestock health and maximizing output. Given the governmental restrictions on green fodder cultivation in Saudi Arabia (SA) due to water conservation efforts, the use of compound feed could serve as a viable alternative for livestock farmers. This study aimed to investigate livestock farmers' farming objectives, their feeding management strategies, and the uptake of compound feed in the country. Data from 650 randomly selected livestock farmers were collected through an online survey with the assistance of the Ministry of Environment, Water and Agriculture. The findings showed that most farmers raised sheep and goats for trade purposes using specialized farms and desert grazing. Alfalfa hay was widely used as a fodder along with barley grain. While approximately 47% of the farmers did not utilize compound feed, 44% reported its usage. Binary logistic regression analysis indicated that formal education, farming experience, and income level significantly influenced the adoption of compound feed among livestock farmers. These results underscore the critical role of education and financial resources in promoting the use of compound feed among livestock farmers in SA. It is recommended that government institutions should develop initiatives to educate farmers on proper animal nutrition practices and provide financial support to make compound feed more affordable for low-income farmers. The widespread use of compound feed has the potential to enhance livestock health and productivity, thereby positively contributing to the food security of SA.
Effect of Donor Cigarette Smoking in Kidney Transplantation: Re-Evaluation of Long-Term Outcomes
Authors: Becker Felix , Pollmann Nicola Sariye , Funke-Kaiser Ricarda , Görlich Dennis , Katou Shadi , Morgül Haluk , Kneifel Felicia , Reuter Stefan , Pascher Andreas , Houben Philipp
Published: June 2024

Cigarette smoking is a common risk factor associated with negative long-term outcomes in kidney transplant recipients. However, whether donor smoking decreases graft longevity or negatively impacts recipient survival after kidney transplantation remains unknown. Therefore, this study aims to investigate the long-term outcome in patients who received a kidney graft from a deceased smoking or non-smoking donor. A total of 580 patients were divided into two groups: patients who received a graft from a smoking donor (n = 276) and those who received a graft from a non-smoking donor (n = 304). Analysis of demographic factors showed that the non-smoking cohort was older, had more extended criteria donors and longer warm ischemia times. The primary composite endpoint of patient and graft survival was better in the smoking donor cohort when analyzed using Kaplan-Meier method but not when controlled for covariates in multivariate analyses. These findings do not support a previously reported negative impact of deceased donor smoking on kidney transplant recipients. Thus, the underlying results should not be interpreted in favor of a positive donor smoking history, but rather remind the transplant community that donor smoking should not be considered as a deciding factor in refusing an otherwise acceptable kidney graft.
Multi-Criteria Decision Support System for Automatically Selecting Photovoltaic Sets to Maximise Micro Solar Generation
Authors: Zanlorenzi Guilherme , Szejka Anderson Luis , Canciglieri Junior Osiris
Published: June 2024

Technological advancements have improved solar energy generation and reduced the cost of installing photovoltaic (PV) systems. However, challenges such as low energy-conversion efficiency and the unpredictability of electricity generation due to shading or climate conditions persist. Despite decreasing costs, access to solar energy generation technologies remains limited. This paper proposes a multi-criteria decision support system (MCDSS) for selecting the most suitable PV set (comprising PV modules, inverters, and batteries) for microgrid installations. The MCDSS employs two multi-criteria decision-making methods (MCDM) for analysis and decision-making: AHP and TOPSIS. The system was tested in two case studies: Barreiras, with a global efficiency of 14.4% and an internal rate of return (IRR) of 56.0%, and Curitiba, with a worldwide efficiency of 14.8% and an IRR of 52.0%. The research provided a framework for assessing and selecting PV sets based on efficiency, cost, and return on investment. Methodologically, it integrates multiple MCDM techniques, demonstrating their applicability in renewable energy. Managerially, it offers a practical tool for decision-makers in the energy sector to enhance the feasibility and attractiveness of microgeneration projects. This research highlights the potential of MCDSS to improve the efficiency and accessibility of solar energy generation.
Development of Static Test Equipment and a System for Lever-Loaded Air Springs
Authors: Zhao Shengli , Zhang Yirui , Qu Baojun , Tian Xiangyu , Zhu Qijun
Published: June 2024

In light of the heavy load applied by traditional air spring test equipment and its complex structural system design, a lever-type torque loading air spring test system is designed. It adopts the principle of Chinese scales to apply the load on the air spring in the form of proportional amplification, which can apply a simulated load on the air spring of 500–800 kg, using the vertical sliding shaft as the transverse limit to make the air spring elongate and compress by 280 mm in the longitudinal direction. The measurement and control system of the test equipment is then developed based on the LabVIEW platform, and the required sensors are selected and installed. The system can achieve real-time data acquisition of the air pressure, load, height and other parameters of the air spring and air spring charging and discharging control. Following the debugging of the function of the test equipment, the function of each subsystem is normal and able to meet the requirements of air spring characteristic and pressure tightness tests. For small spaces, such as laboratories, by reducing the installation of hydraulic and other oil source systems, avoiding the use of large mass blocks to simulate the loading of air spring loads and optimizing the complex installation and debugging process, this miniaturized design for air spring test equipment has benefits for practical applications.
Research Status and Development Trend of Key Technologies for Pineapple Harvesting Equipment: A Review
Authors: He Fengguang , Zhang Qin , Deng Ganran , Li Guojie , Yan Bin , Pan Dexuan , Luo Xiwen , Li Jiehao
Published: June 2024

Pineapple harvesting is a key step in pineapple field production. At present, pineapple fruits are usually picked manually. With decreasing labor resources and increasing production costs, machines have been used instead of manual picking approaches in the modern pineapple industry. This paper briefly describes the basic situation of pineapple planting worldwide. Based on the degree of automation of mechanized pineapple harvesting equipment, the main structural forms, core technologies, and operation modes of semi-automatic, automatic, and intelligent pineapple harvesting equipment are summarized. The research status and existing problems of key pineapple fruit picking robots, such as fruit recognition, maturity classification, positioning, and separation of pineapple fruits, are analyzed. Considering the problems of pineapple harvesting equipment, such as difficulty entering the ground, low harvesting efficiency, low picking success rate, and fruit damage, innovative future research directions for mechanized pineapple harvesting technology are proposed, such as combining agricultural machinery and agronomical principles, integrating mechanized, automated, and intelligent technology, and developing modular designs and generalized approaches.
Reactivating the Potential of Lima Bean (Phaseolus lunatus) for Enhancing Soil Quality and Sustainable Soil Ecosystem Stability
Authors: Abdulraheem Mukhtar Iderawumi , Moshood Abiodun Yusuff , Li Linze , Taiwo Lateef Bamidele , Oyedele Adedayo Omowumi , Ezaka Emmanuel , Chen Hongjun , Farooque Aitazaz A. , Raghavan Vijaya , Hu Jiandong
Published: June 2024

Background: This study explores the role of leguminous crops like lima bean in enhancing soil quality and ecosystem stability. Despite existing studies on agronomic aspects, there is a significant research gap on its impact on soil organic matter level, microbial activity, soil health, and nutrient availability. Therefore, this study examines the capacity of lima bean to reactivate soil quality, focusing on its impact on soil organic matter level, microbial activity, soil health, and nutrient availability. Methods: The experimental area was set up in 2023 using three replicates and a randomized block design. Two treatments were used: lima bean-planted plots and control plots with various weeds and without lima bean. Post-harvest soil samples were collected from various agroecological zones and sterilely packed, and physical, chemical, and biological indices were examined. Results: lima bean significantly affected nutrients, enzymes, soil microbial respiration, and other markers. Amylase activity (0.41**) was positively correlated with urease activity (0.73**), while dehydrogenase activity positively correlated with both. Dehydrogenase activity was negatively correlated with total nitrogen (0.66**) and sulfur (0.60**). Lima bean significantly affected soil quality, with all locations showing higher ratings (55–77%) than wild land, except for location D (Ilora). A total of 70% of total nitrogen variation may be attributed to soil quality (r2 = 0.696). Lima bean enhanced soil quality, potentially enhancing productivity and reducing dependence on inorganic nitrogen inputs. Conclusions: The symbiotic relationship between lima bean and nitrogen-fixing bacteria improves nutrient cycling, enhancing agricultural productivity and environmental conservation. Future research should explore the economic viability of integrating lima bean into crop rotations or agroforestry systems for sustainable agricultural practices, providing valuable information for farmers.
Classification of Apple Color and Deformity Using Machine Vision Combined with CNN
Authors: Qiu Dekai , Guo Tianhao , Yu Shengqi , Liu Wei , Li Lin , Sun Zhizhong , Peng Hehuan , Hu Dong
Published: June 2024

Accurately classifying the quality of apples is crucial for maximizing their commercial value. Deep learning techniques are being widely adopted for apple quality classification tasks, achieving impressive results. While existing research excels at classifying apple variety, size, shape, and defects, color and deformity analysis remain an under-explored area. Therefore, this study investigates the feasibility of utilizing convolutional neural networks (CNN) to classify the color and deformity of apples based on machine vision technology. Firstly, a custom-assembled machine vision system was constructed for collecting apple images. Then, image processing was performed to extract the largest fruit diameter from the 45 images taken for each apple, establishing an image dataset. Three classic CNN models (AlexNet, GoogLeNet, and VGG16) were employed with parameter optimization for a three-category classification task (non-deformed slice–red apple, non-deformed stripe–red apple, and deformed apple) based on apple features. VGG16 achieved the best results with an accuracy of 92.29%. AlexNet and GoogLeNet achieved 91.66% and 88.96% accuracy, respectively. Ablation experiments were performed on the VGG16 model, which found that each convolutional block contributed to the classification task. Finally, prediction using VGG16 was conducted with 150 apples and the prediction accuracy was 90.50%, which was comparable to or better than other existing models. This study provides insights into apple classification based on color and deformity using deep learning methods.
Correction: Riaz et al. Dactyloctenium aegyptium (L.) Willd. (Poaceae) Differentially Responds to Pre- and Post-Emergence Herbicides through Micro-Structural Alterations. Agriculture 2022, 12, 1831
Authors: Riaz Sidra , Basharat Sana , Ahmad Farooq , Hameed Mansoor , Fatima Sana , Ahmad Muhammad Sajid Aqeel , Shah Syed Mohsan Raza , Asghar Ansa , El-Sheikh Mohamed A. , Kaushik Prashant
Published: June 2024

The Agriculture Editorial Office wishes to make the following changes to the author’s paper [...]
Adaptation of Conventional Wheat Flour Mill to Refine Sorghum, Corn, and Cowpea
Authors: Joseph Michael , Alavi Sajid , Adedeji Akinbode A. , Zhu Lijia , Gwirtz Jeff , Thiele Shawn
Published: June 2024

This study evaluated the refinement of sorghum, corn, and cowpea grains using the processing steps and equipment originally designed for wheat milling that consists of a conventional gradual reduction system. The need to mill these grains resulted from a desire to produce alternative ingredients for developing new fortified blended extruded foods used for food aid programming. Milling of white sorghum grain resulted in a crude protein content of 7.4% (wb) for both whole and coarse-milled flour. The crude protein content in whole fine-milled sorghum was 6.8% (wb), which was significantly lower than that of whole coarse flour at 9.3% (wb). A decrease in the ash content of sorghum flour correlates with the decortication process. However, degermed corn, fine and coarse, had significantly different crude protein content of 6.0 ± 0.2% (wb) and 7.7 ± 0.06% (wb), respectively. Degerming of corn improved the quality of corn flour (fine and coarse) by reducing the crude fat content from 3.3 ± 0.18% (wb) to 1.2 ± 0.02% (wb) and 0.6 ± 0.13% (wb), respectively. This helped increase the starch content from 60.1 ± 0.28% (wb) in raw corn to 74.7 ± 0.93% (wb) and 71.8 ± 0.00% (wb) in degermed fine and coarse corn flour, respectively. Cowpea milling did not produce differences in the milling stream outputs when the crude fat and crude protein were compared. Whole flour from the grains had higher milling yields than decorticated flour. This study demonstrated that a mill dedicated to wheat size reduction can be adapted to refine other grains to high quality.
Phenotypic Characterization and Yield Screening of Quinoa Germplasms in Diverse Low-Altitude Regions: A Preliminary Study
Authors: Ren Aixia , Jiang Zhijun , Dai Jing , Sun Min , Anwar Sumera , Tang Peng , Wang Rongzhen , Ding Pengcheng , Li Linghong , Wu Xiangyun , Gao Zhiqiang
Published: June 2024

In this study, 300 quinoa accessions were systematically screened for adaptation to low-altitude areas using seventeen traits. The experiment was conducted in Taigu District, Jinzhong City, Shanxi Province, in 2021, at an altitude of 791 m. Out of the 300 genotypes, 107 were able to produce flowers and fruit, with yields ranging from 538 to 5132 kg ha−1 and with 1000-grain weights between 1.19 g and 2.37 g. These 107 quinoa genotypes were categorized into four groups based on grain yield: below 1500, 1500–2250, 2250–3000, and above 3000 kg ha−1. These groups consisted of 33, 33, 24, and 17 genotypes, respectively. This study found that the 1000-grain weight ranged from 1.19 g to 2.37 g, with an average of 1.72 g, 1.72 g, 1.83 g, and 1.92 g for the respective yield levels. Among the 107 genotypes, 25 had a 1000-grain weight exceeding 2 g, and 13 of these genotypes also had yields exceeding 2250 kg ha−1. The growth period of quinoa genotypes in the low-altitude area was approximately 138–142 days, with longer growth periods associated with higher yield levels. JQ-00084 is the only genotype with a yield > 3000 kg ha−1 and meets all the growth criteria, including a 1000-grain weight exceeding 2 g and a flowering-to-maturity period of over 80 days. Meanwhile, JQ-00315, JQ-00521, JQ-1029, and JQ-02405 fulfilled at least four criteria. These results highlight the importance of germplasm screening for low altitudes, and a large set of germplasms could be screened using the above criteria of phenology, growth, and yield traits.
A Review of Methods for Data-Driven Irrigation in Modern Agricultural Systems
Authors: Jenkins Matthew , Block David E.
Published: June 2024

More than half of global water use can be attributed to crop irrigation, and as the human population grows, so will the water requirements of agriculture. Improved irrigation will be critical to mitigating the impact of increased requirements. An ideal irrigation system is informed by measurements of water demand—a combination of water use and water status signals—and delivers water to plants based on this demand. In this review, examples of methods for monitoring water status are reviewed, along with details on stem and trunk water potential measurements. Then, methods for monitoring evapotranspiration (ET), or water use, are described. These methods are broken into coarse- and fine-scale categories, with a 10 m spatial resolution threshold between them. Fourteen crop ET technologies are presented, including examples of a successful estimation of ET in research and field settings, as well as limitations. The focus then shifts to water distribution technologies, with an emphasis on the challenges associated with the development of systems that achieve dynamic single plant resolution. Some attention is given to the process of choosing ET and water status sensing methods as well as water delivery system design given site characteristics and agronomic goals. This review concludes with a short discussion on the future directions of ET research and the importance of translating findings into useful tools for growers.
Effects of Fungicides on Fungal Development, Conidiophore Morphology, and Conidial Releases from Single Strawberry Powdery Mildew Colonies Assessed Using an Electrostatic Technique
Authors: Takahara Ami , Asano Shunsuke , Kurokawa Minami , Shibata Kanon , Muto Rina , Nonomura Teruo
Published: June 2024

We evaluated the effects of fungicides on strawberry powdery mildew (PM) fungus, Podosphaera aphanis, using an electrostatic technique. Thirty-six fungicides were sprayed on single colonies of P. aphanis on leaves of strawberry seedlings (Fragaria × ananassa Duchesne ex Rozier). Colony development varied depending on the tested fungicides. Particularly, pyraziflumid, triflumizole, triforine, polyoxin, sodium hydrogen carbonate + copper wettable powder, and flutianil + mepanipyrim were highly effective for reducing colony development. P. aphanis colonies were histochemically stained to observe the morphological characteristics of fungal cells forming normal and abnormal conidiophores. Abnormal conidiophores were classified into seven types based on their morphological and cytological characteristics. Finally, asexual conidia were collected from single P. aphanis colonies on the leaves spray-treated with fungicides using a dielectrically polarized insulator plate (electrostatic spore collector); conidia attracted to the insulator plates were counted using a high-fidelity digital microscope. Most tested fungicides highly inhibited the production and/or germination of asexual conidia. The germination of asexual conidia was observed only in thiophanate-methyl (methyl benzimidazole carbamates fungicides; MBC fungicides) and azoxystrobin (quinone outside inhibitors; QoI fungicides). Assessing with the electrostatic technique, we clarified that P. aphanis has developed resistance to both thiophanate-methyl and azoxystrobin. Thus, the methodological assessment analyzing the colony development and the number of conidia released from single colonies will be helpful information for screening effective fungicides.
Impacts of Global Climate Change on Agricultural Production: A Comprehensive Review
Authors: Yuan Xiangning , Li Sien , Chen Jinliang , Yu Haichao , Yang Tianyi , Wang Chunyu , Huang Siyu , Chen Haochong , Ao Xiang
Published: June 2024

Global warming is one of the greatest threats to the social development of human beings. It is a typical example of global climate change, and has profoundly affected human production and life in various aspects. As the foundation of human existence, agricultural production is particularly vulnerable to climate change, which has altered environmental factors such as temperature, precipitation, and wind speed, and affected crop growth cycles, the frequency of extreme weather events, and the occurrence patterns of pests and diseases directly or indirectly, ultimately influencing crop yield and quality. This article reviews the latest research progress in this field, summarizes the impact of global climate change on agricultural production as well as the feedback mechanisms of agricultural activities on climate change, and proposes strategies for agricultural production to cope with global climate change. This paper aims to provide a scientific basis and suggestions for ensuring the sustainable development of agricultural production.