Genomic overview of INA-induced NPR1 targeting and transcriptional cascades in Arabidopsis.

The phytohormone salicylic acid (SA) triggers transcriptional reprogramming that leads to SA-induced immunity in plants. NPR1 is an SA receptor and master transcriptional regulator in SA-triggered transcriptional reprogramming. Despite the indispensable role of NPR1, genome-wide direct targets of NPR1 specific to SA signaling have not been identified. Here, we report INA (functional SA analog)-specific genome-wide targets of Arabidopsis NPR1 in plants expressing GFP-fused NPR1 under its native promoter. Analyses of NPR1-dependently expressed direct NPR1 targets revealed that NPR1 primarily activates genes encoding transcription factors upon INA treatment, triggering transcriptional cascades required for INA-induced transcriptional reprogramming and immunity. We identified genome-wide targets of a histone acetyltransferase, HAC1, including hundreds of co-targets shared with NPR1, and showed that NPR1 and HAC1 regulate INA-induced histone acetylation and expression of a subset of the co-targets. Genomic NPR1 targeting was principally mediated by TGACG-motif binding protein (TGA) transcription factors. Furthermore, a group of NPR1 targets mostly encoding transcriptional regulators was already bound to NPR1 in the basal state and showed more rapid and robust induction than other NPR1 targets upon SA signaling. Thus, our study unveils genome-wide NPR1 targeting, its role in transcriptional reprogramming, and the cooperativity between NPR1, HAC1, and TGAs in INA-induced immunity.

The mutant STAY-GREEN (Cssgr) in cucumber interacts with the CSEP30 protein to elicit a defense response against Podosphaera xanthii.

Disease-resistant plants activate immune responses by specifically recognition Candidate Secreted Effector Proteins (CSEPs) through resistance (R) proteins. In research on cucumber powdery mildew resistance breeding, several R genes and CSEPs have been identified; however, the specific interactions between R proteins and CSEPs are still largely unexplored. In this study, we used a luciferase reporter assay to identify six CSEPs from Podosphaera xanthii that potentially induce cell death in cucumber. Subsequent yeast two-hybrid analysis revealed that only the mature form of CSEP30 (CSEP30∆SP) interacted with the cucumber mutant STAY-GREEN (Cssgr), a gene previously recognized for its broad-spectrum resistance in genetic studies. This interaction was confirmed using pull-down and co-immunoprecipitation assays. Additionally, to determine if the interaction leads to phenotypic changes, Cssgr and CSEP30∆SP were transiently expressed in tobacco leaves. The infiltration of Cssgr in tobacco resulted in reduced chlorosis compared to the wild-type CsSGR. Co-infiltration of Cssgr with CSEP30∆SP induced distinct dry necrotic lesions, contrasting the effects observed when Cssgr and CSEP30∆SP were infiltrated separately. Additionally, after P. xanthii infection in moderately powdery mildew-resistant Gy14 cucumber, similar necrotic lesions and specific expression of Cssgr, as along with defense response-related genes (CsPR1 and CsLecRK6.1), were observed. This study suggests that the interaction between Cssgr and CSEP30∆SP could trigger cell death and defense response, offering new insights into the molecular function of Cssgr in disease resistance in Gy14 cucumber. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01504-6.

Co-application of Parthenium biochar and urea effectively mitigate cadmium toxicity during wheat growth.

Environmental contamination by cadmium (Cd), a highly toxic heavy metal, poses significant health risks to plants and humans. Biochar has been effectively used to promote plant growth and productivity under Cd stress. This study presents an innovative application of biochar derived from the invasive weed Parthenium hysterophorus to promote plant growth and productivity under Cd stress. Our study includes detailed soil and plant analyses, providing a holistic perspective on how biochar and urea amendments influence soil properties, nutrient availability, and plant physiological responses. To address these, we established seven treatments: the control, Cd alone (5 mg kg-1), biochar alone (5 %), urea alone (3 g kg-1), biochar with Cd, urea with Cd, and a combination of biochar and urea with Cd. Cd stress alone significantly reduced plant growth indicators such as shoot and root length, fresh and dry biomass, chlorophyll content, and grain yield. However, the supplementation of biochar, urea, or their combination significantly increased shoot length (by 48%, 34%, and 65%), root length (by 73%, 46%, and 70%), and fresh shoot biomass (by 4%, 31%, and 4%), respectively. This improvement is attributed to enhanced soil properties and improved nutrient absorption. The biochar-urea combination also enhanced Cd tolerance by improving total chlorophyll content by 14 %, 13 %, and 16 % compared to the control, respectively. Similaly, these treatments significantly (p < 0.05) boosted the activity of antioxidant enzymes such as catalase, peroxidase, and superoxide dismutase by 51 %, 30 %, and 51 %, respectively, thereby mitigating oxidative stress as a defensive mechanism. The Cd tolerance was improved by biochar, urea, and their combinations, which reduced Cd content in the shoots (by 60.5 %, 38.9 %, and 51.3 %), roots (by 47.5 %, 23.9 %, and 57.6 %), and grains (by 58.1 %, 30.2 %, and 38.3 %) relative to Cd stress alone, respectively. The synergistic effects of biochar and urea are achieved through improved soil properties, nutrient availability, activating antioxidant defense mechanisms, and minimizing the accumulation of metal ions in plant tissues, thereby enhancing plant defenses against Cd stress. Conclusively, converting invasive Parthenium weed into biochar and combining it with urea offers an environmentally friendly solution to manage its spreading while effectively mitigating Cd stress in crops.

Dose dependent effect of nitrogen on the phyto extractability of Cd in metal contaminated soil using Wedelia trilobata.

Cadmium (Cd) is one of the toxic heavy metal that negatively affect plant growth and compromise food safety for human consumption. Nitrogen (N) is an essential macronutrient for plant growth and development. It may enhance Cd tolerance of invasive plant species by maintaining biochemical and physiological characteristics during phytoextraction of Cd. A comparative study was conducted to evaluate the phenotypical and physiological responses of invasive W. trilobata and native W. chinensis under low Cd (10 µM) and high Cd (80 µM) stress, along with different N levels (i.e., normal 91.05 mg kg-1 and low 0.9105 mg kg-1). Under low-N and Cd stress, the growth of leaves, stem and roots in W. trilobata was significantly increased by 35-23%, 25-28%, and 35-35%, respectively, compared to W. chinensis. Wedelia trilobata exhibited heightened antioxidant activities of catalase and peroxidase were significantly increased under Cd stress to alleviate oxidative stress. Similarly, flavonoid content was significantly increased by 40-50% in W. trilobata to promote Cd tolerance via activation of the secondary metabolites. An adverse effect of Cd in the leaves of W. chinensis was further verified by a novel hyperspectral imaging technology in the form of normalized differential vegetation index (NDVI) and photochemical reflectance index (PRI) compared to W. trilobata. Additionally, W. trilobata increased the Cd tolerance by regulating Cd accumulation in the shoots and roots, bolstering its potential for phytoextraction potential. This study demonstrated that W. trilobata positively responds to Cd with enhanced growth and antioxidant capabilities, providing a new platform for phytoremediation in agricultural lands to protect the environment from heavy metals pollution.

Bacillus altitudinis HNH7 and Bacillus velezensis HNH9 promote plant growth through upregulation of growth-promoting genes in upland cotton.

AIMS: The potential of endophytic Bacillus strains to improve plant growth and yield was evaluated. METHODS AND RESULTS: Endophytic Bacillus altitudinis HNH7 and Bacillus velezensis HNH9 were evaluated for their growth-promoting traits. In an in vitro plate assay, HNH7 and HNH9 exhibited proteolytic, amylolytic, lipolytic and cellulolytic activity. HNH7 and HNH9 were able to solubilize iron by producing siderophores but were unable to solubilize insoluble phosphate. PCR confirmed the presence of four growth-promoting genes viz. pvd, budA, asbA and satA in the genome of HNH7, while HNH9 also possessed the same genes except for budA. In a greenhouse experiment, HNH7 and HNH9 promoted the growth of upland cotton plants by upregulating the expression of growth-linked genes, EXP6, ARF1, ARF18, IAA9, CKX6 and GID1b. However, the expression of genes involved in ethylene biosynthesis, that is ERF and ERF17 was downregulated after treating the plants with HNH7 and HNH9 compared to the control. Furthermore, cotton plants treated with HNH7 and HNH9 exhibited a significantly higher rate of photosynthesis and stomatal conductance. CONCLUSION: HNH7 and HNH9 showed a promising potential to promote the growth of cotton plants. SIGNIFICANCE AND IMPACT OF STUDY: Research on plant growth-promoting Bacillus strains can lead to the formation of biofertilizers.

A Proactive Attack Detection for Heating, Ventilation, and Air Conditioning (HVAC) System Using Explainable Extreme Gradient Boosting Model (XGBoost).

The advent of Industry 4.0 has revolutionized the life enormously. There is a growing trend towards the Internet of Things (IoT), which has made life easier on the one hand and improved services on the other. However, it also has vulnerabilities due to cyber security attacks. Therefore, there is a need for intelligent and reliable security systems that can proactively analyze the data generated by these devices and detect cybersecurity attacks. This study proposed a proactive interpretable prediction model using ML and explainable artificial intelligence (XAI) to detect different types of security attacks using the log data generated by heating, ventilation, and air conditioning (HVAC) attacks. Several ML algorithms were used, such as Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), Ada Boost (AB), Light Gradient Boosting (LGBM), Extreme Gradient Boosting (XGBoost), and CatBoost (CB). Furthermore, feature selection was performed using stepwise forward feature selection (FFS) technique. To alleviate the data imbalance, SMOTE and Tomeklink were used. In addition, SMOTE achieved the best results with selected features. Empirical experiments were conducted, and the results showed that the XGBoost classifier has produced the best result with 0.9999 Area Under the Curve (AUC), 0.9998, accuracy (ACC), 0.9996 Recall, 1.000 Precision and 0.9998 F1 Score got the best result. Additionally, XAI was applied to the best performing model to add the interpretability in the black-box model. Local and global explanations were generated using LIME and SHAP. The results of the proposed study have confirmed the effectiveness of ML for predicting the cyber security attacks on IoT devices and Industry 4.0.

Optimal Path Routing Protocol for Warning Messages Dissemination for Highway VANET.

In vehicular ad hoc networks (VANETs), helpful information dissemination establishes the foundation of communication. One of the significant difficulties in developing a successful dissemination system for VANETs is avoiding traffic fatalities. Another essential success metric is the transfer of reliable and secure warning messages through the shortest path, particularly on highways with high mobility. Clustering vehicles is a general solution to these challenges, as it allows warning alerts to be re-broadcast to nearby clusters by fewer vehicles. Hence, trustworthy cluster head (CH) selections are critical to decreasing the number of retransmissions. In this context, we suggest a clustering technique called Optimal Path Routing Protocol for Warning Messages (OPRP) for dissemination in highway VANETs. OPRP relies on mobility measured to reinforce cluster creation, evade transmission overhead, and sustain message authenticity in a high mobility environment. Moreover, we consider communication between the cluster heads to reduce the number of transmissions. Furthermore, the cluster head is chosen using the median technique based on an odd or even number of vehicles for a stable and lengthy cluster life. By altering traffic densities and speeds, OPRP is compared with prominent schemes. Simulation results revealed that OPRP offers enhanced throughput, end-to-end delay, maximizing packet delivery ratio, and message validity.

Amniotic Fluid Classification and Artificial Intelligence: Challenges and Opportunities.

A fetal ultrasound (US) is a technique to examine a baby's maturity and development. US examinations have varying purposes throughout pregnancy. Consequently, in the second and third trimester, US tests are performed for the assessment of Amniotic Fluid Volume (AFV), a key indicator of fetal health. Disorders resulting from abnormal AFV levels, commonly referred to as oligohydramnios or polyhydramnios, may pose a serious threat to a mother's or child's health. This paper attempts to accumulate and compare the most recent advancements in Artificial Intelligence (AI)-based techniques for the diagnosis and classification of AFV levels. Additionally, we provide a thorough and highly inclusive breakdown of other relevant factors that may cause abnormal AFV levels, including, but not limited to, abnormalities in the placenta, kidneys, or central nervous system, as well as other contributors, such as preterm birth or twin-to-twin transfusion syndrome. Furthermore, we bring forth a concise overview of all the Machine Learning (ML) and Deep Learning (DL) techniques, along with the datasets supplied by various researchers. This study also provides a brief rundown of the challenges and opportunities encountered in this field, along with prospective research directions and promising angles to further explore.

Multiple Sclerosis Diagnosis Using Machine Learning and Deep Learning: Challenges and Opportunities.

Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which can lead to brain, spinal cord, and optic nerve problems. A total of 2.8 million are estimated to suffer from MS. Globally, a new case of MS is reported every five minutes. In this review, we discuss the proposed approaches to diagnosing MS using machine learning (ML) published between 2011 and 2022. Numerous models have been developed using different types of data, including magnetic resonance imaging (MRI) and clinical data. We identified the methods that achieved the best results in diagnosing MS. The most implemented approaches are SVM, RF, and CNN. Moreover, we discussed the challenges and opportunities in MS diagnosis to improve AI systems to enable researchers and practitioners to enhance their approaches and improve the automated diagnosis of MS. The challenges faced by automated MS diagnosis include difficulty distinguishing the disease from other diseases showing similar symptoms, protecting the confidentiality of the patients' data, achieving reliable ML models that are also easily understood by non-experts, and the difficulty of collecting a large reliable dataset. Moreover, we discussed several opportunities in the field such as the implementation of secure platforms, employing better AI solutions, developing better disease prognosis systems, combining more than one data type for better MS prediction and using OCT data for diagnosis, utilizing larger, multi-center datasets to improve the reliability of the developed models, and commercialization.

Using a Deep Learning Model to Explore the Impact of Clinical Data on COVID-19 Diagnosis Using Chest X-ray.

The coronavirus pandemic (COVID-19) is disrupting the entire world; its rapid global spread threatens to affect millions of people. Accurate and timely diagnosis of COVID-19 is essential to control the spread and alleviate risk. Due to the promising results achieved by integrating machine learning (ML), particularly deep learning (DL), in automating the multiple disease diagnosis process. In the current study, a model based on deep learning was proposed for the automated diagnosis of COVID-19 using chest X-ray images (CXR) and clinical data of the patient. The aim of this study is to investigate the effects of integrating clinical patient data with the CXR for automated COVID-19 diagnosis. The proposed model used data collected from King Fahad University Hospital, Dammam, KSA, which consists of 270 patient records. The experiments were carried out first with clinical data, second with the CXR, and finally with clinical data and CXR. The fusion technique was used to combine the clinical features and features extracted from images. The study found that integrating clinical data with the CXR improves diagnostic accuracy. Using the clinical data and the CXR, the model achieved an accuracy of 0.970, a recall of 0.986, a precision of 0.978, and an F-score of 0.982. Further validation was performed by comparing the performance of the proposed system with the diagnosis of an expert. Additionally, the results have shown that the proposed system can be used as a tool that can help the doctors in COVID-19 diagnosis.

The soil pH and heavy metals revealed their impact on soil microbial community.

Soil microbial community is the main indicator having a crucial role in the remediation of polluted soils. These microbes can alter soil pH, organic matter in soils (SOM), soil physic-chemical properties, and potential soil respiration rate via their enzymatic activities. Similarly, heavy metals also have a crucial role in soil enzymatic activities. For this purpose, a number of methods are studied to evaluate the impact of soil pH (a key factor in the formation of biogeographic microbial patterns in bacteria) on bacterial diversity. The effects of pH on microbial activity are glamorous but still unclear. Whereas, some studies also indicate that soil pH alone is not the single key player in the diversity of soil bacteria. Ecological stability is achieved in a pollution-free environment and pH value. The pH factor has a significant impact on the dynamics of microbes' communities. Here, we try to discuss factors that directly or indirectly affect soil pH and the impact of pH on microbial activity. It is also discussed the environmental factors that contribute to establishing a specific bacterial community structure that must be determined. From this, it can be concluded that the environmental impact on soil pH, reducing soil pH and interaction with this factor, and reducing the effect of soil pH on soil microbial community.

Comparative Study of Chinese and American Media Reports on the COVID-19 and Expressions of Social Responsibility: A Critical Discourse Analysis.

Critical discourse analysis aims to explore the dialectical relationship between discourse and ideology. Based on psycholinguistic research, this paper analyzes the Chinese and American media's news reports and comments on the COVID-19. It aims to expose the hidden psychological messages and ideologies behind the words. The corpus in this paper is mainly from the official media of China Daily and Time from December 2019 to January 2021 in China and the United States. This paper uses Wang Zhenhua's Appraisal Theory and Halliday's Systemic Functional Grammar as tools to make a comparative analysis of the corpus. At the textual level, languages are classified and lexical choices are analyzed followed by the analysis of the reporter's ideology after reviewing the motivation of the reporters of two countries. On the level of social responsibility expression and discourse, the paper analyzes the news reports, which are characterized by the combination of the reporter's views on the news. In the aspect of social practice, the social and cultural factors and background of news reports are analyzed. China calls for strengthening cooperation and exchanges with other countries to jointly fight the epidemic. The Chinese government has actively shared its experience and made corresponding contributions to international economic recovery. However, the US government shirks its responsibility by claiming that the effective implementation of Chinese methods and experience in China does not mean that it can achieve corresponding results in Europe and the US. At the same time, the United States provides medical supplies to other countries. This study hopes to help awaken readers' critical thinking and increase their awareness of the anti-control of mass discourse. At the same time, it is hoped that readers can view the epidemic from a more scientific perspective, understand the facts and reject the unwarranted panic. It will also help reshape Chinese and American discourse.

Identification and analysis of a differentially expressed wheat RING-type E3 ligase in spike primordia development during post-vernalization.

KEY MESSAGE: We identified a RING-type E3 ligase (TaBAH1) protein in winter wheat that targets TaSAHH1 for degradation and might be involved in primordia development by regulating targeted protein degradation. Grain yield per spike in wheat (Triticum aestivum), is mainly determined prior to flowering during mature primordia development; however, the genes involved in primordia development have yet to be characterized. In this study, we demonstrated that, after vernalization for 50 days at 4 °C, there was a rapid acceleration in primordia development to the mature stages in the winter wheat cultivars Keumgang and Yeongkwang compared with the Chinese Spring cultivar. Although Yeongkwang flowers later than Keumgang under normal condition, it has the same heading time and reaches the WS9 stage of floral development after vernalization for 50 days. Using RNA sequencing, we identified candidate genes associated with primordia development in cvs. Keumgang and Yeongkwang, that are differentially expressed during wheat reproductive stages. Among these, the RING-type E3 ligase TaBAH1 (TraesCS5B01G373000) was transcriptionally upregulated between the double-ridge (WS2.5) stage and later stages of floret primordia development (WS10) after vernalization. Transient expression analysis indicated that TaBAH1 was localized to the plasma membrane and nucleus and was characterized by self-ubiquitination activity. Furthermore, we found that TaBAH1 interacts with TaSAHH1 to mediate its polyubiquitination and degradation through a 26S proteasomal pathway. Collectively, the findings of this study indicate that TaBAH1 might play a prominent role in post-vernalization floret primordia development.

E-Triage Systems for COVID-19 Outbreak: Review and Recommendations.

With population growth and aging, the emergence of new diseases and immunodeficiency, the demand for emergency departments (EDs) increases, making overcrowding in these departments a global problem. Due to the disease severity and transmission rate of COVID-19, it is necessary to provide an accurate and automated triage system to classify and isolate the suspected cases. Different triage methods for COVID-19 patients have been proposed as disease symptoms vary by country. Still, several problems with triage systems remain unresolved, most notably overcrowding in EDs, lengthy waiting times and difficulty adjusting static triage systems when the nature and symptoms of a disease changes. In this paper, we conduct a comprehensive review of general ED triage systems as well as COVID-19 triage systems. We identified important parameters that we recommend considering when designing an e-Triage (electronic triage) system for EDs, namely waiting time, simplicity, reliability, validity, scalability, and adaptability. Moreover, the study proposes a scoring-based e-Triage system for COVID-19 along with several recommended solutions to enhance the overall outcome of e-Triage systems during the outbreak. The recommended solutions aim to reduce overcrowding and overheads in EDs by remotely assessing patients' conditions and identifying their severity levels.

Applications of Big Data Analytics to Control COVID-19 Pandemic.

The COVID-19 epidemic has caused a large number of human losses and havoc in the economic, social, societal, and health systems around the world. Controlling such epidemic requires understanding its characteristics and behavior, which can be identified by collecting and analyzing the related big data. Big data analytics tools play a vital role in building knowledge required in making decisions and precautionary measures. However, due to the vast amount of data available on COVID-19 from various sources, there is a need to review the roles of big data analysis in controlling the spread of COVID-19, presenting the main challenges and directions of COVID-19 data analysis, as well as providing a framework on the related existing applications and studies to facilitate future research on COVID-19 analysis. Therefore, in this paper, we conduct a literature review to highlight the contributions of several studies in the domain of COVID-19-based big data analysis. The study presents as a taxonomy several applications used to manage and control the pandemic. Moreover, this study discusses several challenges encountered when analyzing COVID-19 data. The findings of this paper suggest valuable future directions to be considered for further research and applications.

Smokeless tobacco use and risk of oral cavity cancer

Background/aim/AIM: Smokeless tobacco has been associated with oral cavity cancer for several decades. The incidence of oral cavity cancer is higher in some parts of the world especially South and South-East Asia including Pakistan. The aim of current study was to evaluate the risk of oral cavity cancer among smokeless tobacco users in our country. Materials and methodsAND METHODS: A case-control study was conducted between November 2016 and September 2017. Patients diagnosed with oral cavity cancer receiving treatment were included as cases and the attendants of various cancer patients visiting the hospital during the study period were included in the study as controls. Odds ratios (OR) and 95% confidence intervals (CI) were calculated and all reported P-values were considered significant at < 0.05. Results: The crude OR for the "ever smokeless tobacco users" among cases and controls came out to be 4.98 (95%CI; 2.76­9.01). The OR for snuff users among cases and controls was 4.82 (95%CI; 2.37­9.80) and that for betel leaf users was 4.42 (95%CI; 1.66­11.91) after adjusting for smoking and age. Conclusion: Our study provided strong evidence for snuff and betel leaf to be independent risk factors for oral cavity cancer.

THE Role of Preoperative carcinoembryonic antigen in recurrence of resectable colorectal carcinoma.

In colorectal carcinoma, carcinoembryonic antigen (CEA) is a recommended marker for surveillance after curative resection. The aim of the present study was to determine the association of preoperative CEA with recurrence of colorectal carcinoma in our population. The study included 55 patients with all operable stages of colorectal adenocarcinoma treated during the 2012-2014 period, evaluated retrospectively and followed-up for recurrence for 2 years. Data on the baseline (preoperative) CEA levels were retrieved from patient files. On data analysis, SPSS 16.0 was used. In patients with normal preoperative CEA, the rate of recurrence was significantly low (p=0.008) and the likelihood of no recurrence 1.55-fold greater as compared to patients with raised initial CEA levels (p=0.028). In patients with raised preoperative CEA, the risk of recurrence was 5.26-fold greater as compared to those with normal CEA levels (p=0.028). A significant weak positive correlation (rs=0.297) was found between raised CEA and recurrence. A highly significant (p=0.002) moderate positive correlation was recorded in patients aged <50 and moderate positive correlation of borderline significance in males (rs=0.324, p=0.058). Sensitivity was 94.4% and specificity 32.4% in predicting recurrence. Accordingly, preoperative elevated CEA showed a significant weak positive correlation with recurrence while normal preoperative CEA moderately decreased the likelihood of recurrence.

Synthesis, Characterization, and in Vitro Anticancer Activity of Copper and Zinc Bis(Thiosemicarbazone) Complexes.

A series of eight bis(thiosemicarbazone) ligands and 16 of their respective copper(II) and zinc(II) complexes containing a combination of hydrogen, methyl, pyridyl, phenyl, and/or ethyl substituents at the diimine position of the ligand backbone were synthesized and characterized. The objective of this study was to identify the structure-activity relationships within a series of analogues with different substituents at the diimine position of the backbone and at the terminal N atom. The Cu(II) complexes Cu(GTSM2), Cu(GTSCM), Cu(PyTSM2), Cu(EMTSM2) and Cu(PGTSM2) demonstrated a distorted square planar geometry, while the Zn(II) complexes Zn(ATSM2)(DMSO), Zn(PyTSM2)(DMSO), and Zn(PGTSM2)(H2O) formed a distorted square pyramidal geometry. Cyclic voltammetry showed that the Cu(II) complexes display quasi-reversible electrochemistry. Of the agents, Cu(II) glyoxal bis(4,4-dimethyl-3-thiosemicarbazone) [Cu(GTSM2)] and Cu(II) diacetyl bis(4,4-dimethyl-3-thiosemicarbazone) [Cu(ATSM2)] demonstrated the greatest antiproliferative activity against tumor cells. Substitutions at the diimine position and at the terminal N atom with hydrophobic moieties markedly decreased their antiproliferative activity. Complexation of the bis(thiosemicarbazones) with Zn(II) generally decreased their antiproliferative activity, suggesting the Zn(II) complex did not act as a chaperone to deliver the ligand intracellularly, in contrast to similar bis(thiosemicarbazone) cobalt(III) complexes [King et al. Inorg. Chem. 2017, 56, 6609-6623]. However, five of the eight bis(thiosemicarbazone) Cu(II) complexes maintained or increased their antiproliferative activity, relative to the ligand alone, and a mechanism of Cu-induced oxidative stress is suggested. Surprisingly, relative to normoxic growth conditions, hypoxia that is found in the tumor microenvironment decreased the antiproliferative efficacy of most bis(thiosemicarbazones) and their copper complexes. This was independent of the potential hypoxia-selectivity mediated by Cu(II/I) redox potentials. These results provide structure-activity relationships useful for the rational design of bis(thiosemicarbazone) anticancer agents.

Identification of novel rice (Oryza sativa) HPP and HIPP genes tolerant to heavy metal toxicity.

HPP (heavy metal associated plant protein) and HIPP (heavy metal associated isoprenylated plant protein) are a group of metal-binding metallochaperones playing crucial roles in metal homeostasis and detoxification. Up to now, only few of them have been functionally identified in plants. Here, we identified 54 HPP and HIPP genes in rice genome. Analysis of the transcriptome datasets of the rice genome exposed to cadmium (Cd) revealed 17 HPP/HIPP genes differentially expressed, with 11 being upregulated (>2 fold change, p < 0.05). Comprehensive analysis of transcripts by qRT-PCR showed that both types of genes displayed diverse expression pattern in rice under excess manganese (Mn), copper (Cu) and Cd stress. Multiple genomic analyses of HPPs/HIPPs including phylogenesis, conserved domains and motifs, genomic arrangement and genomic and tandem duplication were performed. To identify the role of the genes, OsHIPP16, OsHIPP34 and OsHIPP60 were randomly selected to express in yeast (Saccharomyces cerevisiae) mutants pmrl, cup2, ycf1 and zrc1, exhibiting sensitivity to Mn, Cu, Cd and Zn toxicity, respectively. Complementation test showed that the transformed cells accumulated more metals in the cells, but their growth status was improved. To confirm the functional role, two mutant oshipp42 lines defective in OsHIPP42 expression were identified under metal stress. Under normal condition, no difference of growth between the oshipp42 mutant and wild-type plants was observed. Upon excess Cu, Zn, Cd and Mn, the oshipp42 lines grew weaker than the wild-type. Our work provided a novel source of heavy metal-binding genes in rice that can be potentially used to develop engineered plants for phytoremediation in heavy metal-contaminated soils.

Biological and biochemical characteristics of male reproductive system, serum metabolites and carcass quality of Japanese quails by the supplementation of Pinus ponderosa leaves and α-tocopherol acetate.

The aim of the current study was to evaluate the effect of dietary supplementation of Pinus ponderosa leaves (pine leaves) and α-tocopherol acetate (vitamin E) powder on male reproductive system, serum metabolites and carcass characteristics of Japanese quails. A total of 360-day-old male quails were purchased from the open market and kept at poultry shed for ninety-four days. After ten days of adaptation, all quails were randomly assigned into 4 groups, control (IC); supplemented with α-tocopherol acetate (IE) at the rate of 150 mg/L; Pinus ponderosa leaves (IP) at the rate of 150 mg/L; and 70 mg α-tocopherol acetate and 70 mg Pinus ponderosa leaves (IEP). Pinus ponderosa leaves and α-tocopherol acetate supplementation had not significantly (p > .05) effected on final body weight gain, feed intake and feed conversion ratio of quails. The high-density lipoprotein cholesterol (HDLC) and total cholesterol (TC) were significantly (p > .05) affected by IE and IP groups as compared to IC and IEP groups. Triglyceride (TG), glutathione peroxidase (GPx) and superoxide dismutase (SOD) significantly (p < .05) increased in all treatment groups except for the IC group. Aspartate transaminase (AST) significantly (p > .05) decreased in treatment groups as compared to control group. Overall, the mineral levels significantly (p < .05) increased in treatment groups as compared to control. Cloacal gland index values, the quantity of foam production and testis weight were significantly (p < .05) increased in treatment groups. It was concluded that the supplementation of Pinus ponderosa leaves and α-tocopherol acetate improved the testis weight, foam production, serum antioxidant enzymes and mineral level especially zinc in Japanese quail considered an indicative characteristic of higher sperm production rate and improved sexual activity. Further, higher gametogenesis rate, sperm production or reproductive behaviour including different hormonal level will be analysed in future study.