Clinical and genetic investigation of 14 families with various forms of short stature syndromes.

Skeletal dysplasias are a heterogeneous group of disorders presenting mild to lethal defects. Several factors, such as genetic, prenatal, and postnatal environmental may contribute to reduced growth. Fourteen families of Pakistani origin, presenting the syndromic form of short stature either in the autosomal recessive or autosomal dominant manner were clinically and genetically investigated to uncover the underlying genetic etiology. Homozygosity mapping, whole exome sequencing, and Sanger sequencing were used to search for the disease-causing gene variants. In total, we have identified 13 sequence variants in 10 different genes. The variants in the HSPG2 and XRCC4 genes were not reported previously in the Pakistani population. This study will expand the mutation spectrum of the identified genes and will help in improved diagnosis of the syndromic form of short stature in the local population.

E3 ubiquitin ligase UBR5 modulates circadian rhythm by facilitating the ubiquitination and degradation of the key clock transcription factor BMAL1.

The circadian clock is the inner rhythm of life activities and is controlled by a self-sustained and endogenous molecular clock, which maintains a ~ 24 h internal oscillation. As the core element of the circadian clock, BMAL1 is susceptible to degradation through the ubiquitin-proteasome system (UPS). Nevertheless, scant information is available regarding the UPS enzymes that intricately modulate both the stability and transcriptional activity of BMAL1, affecting the cellular circadian rhythm. In this work, we identify and validate UBR5 as a new E3 ubiquitin ligase that interacts with BMAL1 by using affinity purification, mass spectrometry, and biochemical experiments. UBR5 overexpression induced BMAL1 ubiquitination, leading to diminished stability and reduced protein level of BMAL1, thereby attenuating its transcriptional activity. Consistent with this, UBR5 knockdown increases the BMAL1 protein. Domain mapping discloses that the C-terminus of BMAL1 interacts with the N-terminal domains of UBR5. Similarly, cell-line-based experiments discover that HYD, the UBR5 homolog in Drosophila, could interact with and downregulate CYCLE, the BMAL1 homolog in Drosophila. PER2-luciferase bioluminescence real-time reporting assay in a mammalian cell line and behavioral experiments in Drosophila reveal that UBR5 or hyd knockdown significantly reduces the period of the circadian clock. Therefore, our work discovers a new ubiquitin ligase UBR5 that regulates BMAL1 stability and circadian rhythm and elucidates the underlying molecular mechanism. This work provides an additional layer of complexity to the regulatory network of the circadian clock at the post-translational modification, offering potential insights into the modulation of the dysregulated circadian rhythm.

Decision algorithm for educational institute selection with spherical fuzzy heronian mean operators and Aczel-Alsina triangular norm.

This article presents a novel study of spherical fuzzy sets (SFSs), a more comprehensive framework of intuitionistic fuzzy sets and picture fuzzy sets. The SFS allows the decision-makers (DMs) to cope with complicated and insufficient information during the aggregation process. The Heronian mean (HrM) model theory is also utilized to express correlation among different input arguments or characteristics. Recently, the theory of Aczel Alsina triangular norms gained a lot of attention from various research scholars and has many capabilities to provide smooth approximations during decision analysis. In this article, we developed some appropriate operations of Aczel Alsina t-norms and t-conorms in light of spherical fuzzy (SF) information. We develop new mathematical ways to look at SF data to keep clarity and sufficient information. These are the SF Aczel Alsina Heronian mean (SFAAHrM) and SF Aczel Alsina weighted Heronian mean (SFAAWHrM) operators. Furthermore, we also present a list of new strategies based on Aczel Alsina operations, such as SF Aczel Alsina geometric Heronian mean (SFAAGHrM) and SF Aczel Alsina weighted geometric Heronian mean (SFAAWGHrM) operators. Some notable properties are also characterized to show the validity and effectiveness of our derived mathematical approaches. Considering our derived strategies, an algorithm for the multiple attribute decision-making (MADM) problem is established to resolve complicated real-life applications. A numerical example presents the compatibility of derived approaches and provides a solid mechanism to improve the performance of educational institutes. A comparison technique is also demonstrated to show the applicability and consistency of diagnosed approaches by contrasting the findings of pioneered approaches with existing methodologies.

Aczel-Alsina T-norm based group decision-making technique for the evaluation of electric cars using generalized orthopair fuzzy aggregation information with unknown weights.

Data management and finding precise outcomes from large amounts of information are among the biggest challenges for scientists. The technique of multi-attribute group decision-making (MAGDM) is a valuable tool for investigating fuzzy data precisely. The key objective of the paper is to redefine the q-rung orthopair (q-RO) fuzzy set (FS) (q-ROFS) in the term of interval-valued and proposed new aggregation operators (AOs) based on the Aczel-Alsina (AA) t-norm (TN) and t-conorm (TCN) operations. The AA operational laws are a generalized form of existing TNs and TCNs and give more reliable results because they can fluctuate in their parametric values. The concept of interval-valued enlarges the space of membership degree (MD) and non-membership degree (NMD) for decision-makers. By taking qth power, the interval-valued q-ROFS (IV-q-ROFS) structure. The IV-q-ROFS can handle the uncertainty and vagueness in data, then interval-valued intuitionistic FS (IV-IFS) and interval-valued Pythagorean FS (PyFS) (IV-PyFS) and provide accurate results. The thought of power AOs (PAOs) makes the relationship between weight vectors and reduces the chances of uncertainty in aggregated results. By taking advantage of PAOs, this article is devoted to introducing the interval-valued q-ROF Aczel-Alsina power-weighted averaging (IV-q-ROFAAPWA) and interval-valued q-ROF Aczel-Alsina power-weighted geometric (IV-q-ROFAAPWG) operators. The fundamental axioms of AOs, idempotency, boundedness, and monotonicity, are also discussed. To illustrate the importance of suggested AOs, the real-life problem of electric car selection was solved by applying the MAGDM method using the proposed IV-q-ROFAAPWA and IV-q-ROFAAPWG operators. The comparison of proposed AOs with currently present AOs is also part of the article. We finally constructed solid conclusions.

Decision algorithm for picture fuzzy sets and Aczel Alsina aggregation operators based on unknown degree of wights.

Aggregation operators (AOs) are well-known and efficient mathematical tools that are utilized to overcome the impact of imprecise and vague information during the aggregation process. The theoretical concepts of Aczel Alsina aggregation expressions are an extension of triangular norms and become a hot research topic in the environment of the fuzzy framework. The power operators provide a smooth approximation and are used to mitigate the influence of redundant or insufficient information on the attributes or criteria. Some robust aggregation approaches are developed by combining two different theories, like power operators and Aczel Alsina aggregation tools. This article aims to explore the theory of picture fuzzy sets (PFSs), an extended version of fuzzy sets, and intuitionistic fuzzy sets. Some robust operations of Aczel Alsina aggregation tools are also present in light of the picture fuzzy environment. We established a class of new methodologies in the light of picture fuzzy information, including picture fuzzy Aczel Alsina power weighted average (PFAAPWA) and picture fuzzy Aczel Alsina power ordered weighted average (PFAAPOWA) operators. We also developed an appropriate approach like picture fuzzy Aczel Alsina power weighted geometric (PFAAPWG) and picture fuzzy Aczel Alsina power ordered weighted geometric (PFAAPOWG) operators. Notable properties and characteristics of proposed methodologies are also demonstrated. Our invented approaches not only aggregate complicated information but can clearly define interrelationships among several arguments. Moreover, we establish an algorithm for the multi-attribute group decision-making (MAGDM) problem to handle the impact of redundant and vague information on human opinions. Finally, we study an experimental case study to evaluate an appropriate optimal option from available options. To reveal consistency and effectiveness of developed approaches, influence study by changing various parametric values and comparative study by comparing results of existing approaches.

Multi-attribute decision-making method based on complex T-spherical fuzzy frank prioritized aggregation operators.

This article aims to introduce new aggregation operators (AOs) by assigning the positive real values known as priority degree among the strict priority levels. To Develop the complex T-spherical fuzzy (TSF) frank prioritized (CTSFFP) AOs, using the frank t-norm (FTN) and frank t-conorm (FTCN) operational laws, also explain sum, product, and power operations under complex TSF information. The TSF set framework has a superior structure for uncertain data handling than an existing intuitionistic fuzzy set (FS), Pythagorean FS (PyFS), q-rung orthopair FS (q-ROFS), picture FS (PFS), and spherical FS (SFS). Because the structure of the TSF set has the most generalized form of IFS, PyFS, q-ROFS, PFS, and SFS, it provides greater freedom to decision experts for handling information where these discussed sets fail to aggregate ambiguous details. Utilizing the idea of priority degree, proposed new AOs called CTSFFP weighted averaging (CTSFFPWA), CTSFFP ordered weighted averaging (CTSFFPOWA), CTSFFP hybrid weighted averaging (CTSFFPHWA), CTSFFP weighted geometric (CTSFFPWG), CTSFFP ordered weighted geometric (CTSFFPOWG), CTSFFP hybrid weighted geometric (CTSFFPHWG) operators. Some desirable properties of AOs, such as idempotency, monotonicity, and boundedness, are also discussed. To show the importance of proposed AOs, the real-life problem of multi-attribute decision-making (MADM) is solved with the help of developed CTSFFPWA and CTSFFPWG operators. To enhance the proposed AOs' superiority, compare the diagnosed theory with existing AOs and give conclusions.

Exploring the reasons for defaulting from childhood immunization: a qualitative study in Pakistan.

BACKGROUND: Childhood vaccination is widely recognized as the most effective means to prevent various diseases. However, a considerable amount of children still miss out on their vaccination schedules. Therefore, this study explores the reasons for defaulting from the expanded program on immunization in district Swat, Pakistan. METHODS: A qualitative phenomenological approach was used. Data collection took place from March to September 2022. Thirty-six in-depth interviews were conducted with participants who had defaulter children. The collected qualitative data were analysed thematically to identify key patterns and themes related to the reasons for defaulting from childhood vaccination schedules. RESULTS: Six themes emerged, i.e., illness of the defaulter child at the scheduled time, perceived side effects of the vaccination, factors related to caregivers, myths and misconceptions, vaccinators attitudes and crowed vaccination centres, as well as poor immunization service arrangements. Four subthemes arose related to caregivers, such as lack of clear understanding about completion of vaccination, least priority for child's vaccination, cultural restriction on mothers, and the loss of vaccination card. CONCLUSION: According to the study's findings, caregivers have their own perceptions regarding the non-completion of their children's vaccination schedule. The childhood immunization defaulting arises from various factors including child illness, Adverse Events Following Immunization (AEFIs) concerns, misconceptions, improper injection techniques, and negative vaccinator attitudes. The vaccination completion rate may be increased if the concerns of the caregivers are appropriately addressed.

Higher cadmium and zinc accumulation in parsley (Petroselinum crispum) roots activates its antioxidants defense system.

Parsley (Petroselinum crispum) is herb with many biological and medicinal benefits for humans. However, growth on zinc (Zn) and cadmium (Cd) contaminated sites might get severely affected due to over accumulation of heavy metals (HM) in different plant tissues. Antioxidants play a crucial role in minimizing the negative effects of HM. The present study investigates the effects of Zn and Cd stress on P. crispum morphological parameters, enzymatic/non-enzymatic antioxidant profiling and metal accumulation in shoot/root. Plants were exposed to different concentrations of Zn (50, 100, 150 and 200 µM) and Cd (10, 20, 40 and 80 µM) along with control (no stress), in soil-less Hoagland's solution. The results showed that Zn and Cd substantially decrease the growth parameters with increased contents of malondialdehyde (MDA), hydrogen peroxide (H2O2), and electrolyte leakage (EL). Non-enzymatic antioxidant activities, like total phenolic contents (TPC) and ferric reducing antioxidant power (FRAP), were induced high in leaves only upon Cd stress and contrarily decreased upon Zn stress. Total flavonoid contents (TFC) were decreased under Zn and Cd stress. Enzymatic antioxidant activities like superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) were also strongly induced upon Cd stress. At the same time, SOD and guaiacol peroxidase (GPX) activity was induced significantly upon Zn stress. Cd uptake and accumulation was notably high in roots as compared to shoots, which suggests P. crispum have a reduced ability to translocate Cd towards aboveground parts (leaves). Additionally, strong induction of antioxidants by P. crispum under Cd stress might indicate the capacity to effectively re-modulate its physiological response. However, further investigations regarding other HMs and experiments at the molecular level are still needed.

Multi-attribute group decision-making based on Pythagorean fuzzy rough Aczel-Alsina aggregation operators and its applications to Medical diagnosis.

The fusion of information is a very hectic process whenever we analyze the information. Several frameworks have been introduced to reduce the uncertainty while fusing the information. Among those techniques, the Pythagorean fuzzy rough set (PyFRS), which is based on approximations is a key idea for dealing with uncertainty when data is taken from real-world circumstances. Furthermore, the most adaptable and flexible operational laws based on the parameters for fuzzy frameworks are Aczel-Alsina t-norm (AATNM) and Aczel-Alsina t-conorm (AATCNM). The major goal of this work is to introduce some methods for the basic operations of the information in the shape of Pythagorean fuzzy rough (PyFR) values (PyFRVs). Consequently, the PyFR Aczel-Alsina weighted geometric (PyFRAAWG), PyFR Aczel-Alsina ordered weighted geometric (PyFRAAOWG), and PyFR Aczel-Alsina hybrid weighted geometric (PyFRAAHWG) operators are developed in this article based on AATNM and AATCNM. Further, some basic properties of the developed operators are observed and discussed. Further, the developed approaches are applied to the problem of multi-attribute group decision-making (MAGDM). The obtained results from the MAGDM problem are observed at various values of the parameters involved by AATNM and AATCNM. Moreover, the results are also compared with already existing techniques for the significance of the developed approach.

Variants in EFCAB7 underlie nonsyndromic postaxial polydactyly.

Polydactyly is the most common limb malformation that occurs in 1.6-10.6 per one thousand live births, with incidence varying with ancestry. The underlying gene has been identified for many of the ~100 syndromes that include polydactyly. While for the more common form, nonsydromic polydactyly, eleven candidate genes have been reported. We investigated the underlying genetic cause of autosomal recessive nonsyndromic postaxial polydactyly in four consanguineous Pakistani families. Some family members with postaxial polydactyly also present with syndactyly, camptodactyly, or clinodactyly. Analysis of the exome sequence data revealed two novel homozygous frameshift deletions in EFCAB7: [c.830delG;p.(Gly277Valfs*5)]; in three families and [c.1350_1351delGA;p.(Asn451Phefs*2)] in one family. Sanger sequencing confirmed that these variants segregated with postaxial polydactyly, i.e., family members with postaxial polydactyly were found to be homozygous while unaffected members were heterozygous or wild type. EFCAB7 displays expressions in the skeletal muscle and on the cellular level in cilia. IQCE-EFCAB7 and EVC-EVC2 are part of the heterotetramer EvC complex, which is a positive regulator of the Hedgehog (Hh) pathway, that plays a key role in limb formation. Depletion of either EFCAB7 or IQCE inhibits induction of Gli1, a direct Hh target gene. Variants in IQCE and GLI1 have been shown to cause nonsyndromic postaxial polydactyly, while variants in EVC and EVC2 underlie Ellis van Creveld and Weyers syndromes, which include postaxial polydactyly as a phenotype. This is the first report of the involvement of EFCAB7 in human disease etiology.

A variant in the LDL receptor-related protein encoding gene LRP4 underlying polydactyly and phalangeal synostosis in a family of Pakistani origin.

A family of Pakistani origin, segregating polydactyly, and phalangeal synostosis in an autosomal dominant manner, has been investigated and presented in the present report. Whole-exome sequencing (WES), followed by segregation analysis using Sanger sequencing, revealed a heterozygous missense variant [c.G1696A, p.(Gly566Ser)] in the LRP4 gene located on human chromosome 11p11.2. Homology protein modeling revealed the mutant Ser566 generated new interactions with at least four other amino acids and disrupted protein folding and function. Our findings demonstrated the first direct evidence of involvement of LRP4 in causing polydactyly and phalangeal synostosis in the same family. This study highlighted the importance of inclusion of LRP4 gene in screening individuals presenting polydactyly in hands and feet, and phalangeal synostosis in the same family.

Complex spherical fuzzy Aczel Alsina aggregation operators and their application in assessment of electric cars.

The multi-criteria decision-making (MCDM) tool is a robust decision-making technique utilized in several fields like networking, risk management, digital analysis, cybercrime investigation, artificial intelligence, waste management enterprises and many other selection criteria. Complex SFS (CSFS) is a new edition of the spherical fuzzy set (SFS) that offers substantial information about any item in terms of amplitude and phase terms in a wider range of real terms. Complex SFS (CSFS) can be an extension of the spherical fuzzy set (SFS). The Aczel-Alsina aggregation tools are more appropriate aggregation operators (AOs), and they are used to conquer the impact of inconsistent and uncertain data. In this paper, we reveal some new approaches based on Aczel-Alsina aggregation tools under consideration of Complex Spherical Fuzzy (CSF) information. These new approaches include the CSF Aczel-Alsina weighted average (CSFAWA) operator, and the CSF Aczel-Alsina ordered weighted average (CSFOWA) operator. In addition to this, we also introduce a list of novel techniques by making use of the theory of Aczel-Alsina aggregation tools such as CSF Aczel-Alsina weighted geometric (CSFAWG) and CSF Aczel-Alsina ordered weighted geometric (CSFOWG) operators. To demonstrate the resilience and efficacy of the approaches that have been mentioned, we will examine a few exceptional examples and remarkable properties of the methodology that we have devised. In addition, a characterization is provided for an approach to the MCDM issue using the CPF information system. We use the example of electric automobiles as a case study to illustrate the uniformity and dependability of the methodology that we have established. This example was chosen because of the high cost of fuel and the present economic challenges that are being encountered by families in the middle class. An empirical case study is also constructed to determine an electric car that is desirable based on the techniques that we have proposed. To evaluate the correctness and superiority of the established strategies, we compare the outcomes of previously used techniques with the AOs currently being provided.

The symmetric and asymmetric impacts of green energy, eco-innovation, and urbanization in explaining low-carbon economy for Pakistan.

Over the past three decades, global economic development patterns have considerably affected the natural environment, and economies have endured a plethora of environmental concerns as a result of the negative effects of climate change. Among them, Pakistan is the fifth most vulnerable country, and climate change has harmfully affected the ecological and socio-economic conditions of the country. In this regard, this study aimed to investigate the role of green energy consumption, eco-innovation, and urbanization while explaining the dream of low-carbon economy and environmental sustainability in the context of Pakistan using annual time series dataset spanning from 1990 to 2020. The short-run and long-run associations among explained and explanatory variables were investigated using the symmetric, asymmetric, and quantile autoregressive distributed lag models. The findings of the study demonstrated that low-carbon economy, green energy consumption, ecological innovation, urbanization, GDP per capita, and labor force are cointegrated for the long-term association in symmetric, asymmetric, and quantile autoregressive distributed lag models. Furthermore, green energy consumption and effective eco-innovation are the most important paths to ensure environmental sustainability, while urbanization, GDP per capita, and labor force contribute negatively to the low-carbon economy. The findings of the study provide a policy framework for the development of a comprehensive strategy to promote environmental sustainability in Pakistan by emphasizing green energy consumption, ecological innovation, and controlled urbanization, as well as the incorporation of environment friendly policies into economic development policies.

Applications of the Multiattribute Decision-Making for the Development of the Tourism Industry Using Complex Intuitionistic Fuzzy Hamy Mean Operators.

In the aggregation of uncertain information, it is very important to consider the interrelationship of the input information. Hamy mean (HM) is one of the fine tools to deal with such scenarios. This paper aims to extend the idea of the HM operator and dual HM (DHM) operator in the framework of complex intuitionistic fuzzy sets (CIFSs). The main benefit of using the frame of complex intuitionistic fuzzy CIF information is that it handles two possibilities of the truth degree (TD) and falsity degree (FD) of the uncertain information. We proposed four types of HM operators: CIF Hamy mean (CIFHM), CIF weighted Hamy mean (CIFWHM), CIF dual Hamy mean (CIFDHM), and CIF weighted dual Hamy mean (CIFWDHM) operators. The validity of the proposed HM operators is numerically established. The proposed HM operators are utilized to assess a multiattribute decision-making (MADM) problem where the case study of tourism destination places is discussed. For this purpose, a MADM algorithm involving the proposed HM operators is proposed and applied to the numerical example. The effectiveness and flexibility of the proposed method are also discussed, and the sensitivity of the involved parameters is studied. The conclusive remarks, after a comparative study, show that the results obtained in the frame of CIFSs improve the accuracy of the results by using the proposed HM operators.

Correction: In silico screening and identification of deleterious missense SNPs along with their effects on CD-209 gene: An insight to CD-209 related-diseases.

[This corrects the article DOI: 10.1371/journal.pone.0247249.].

Biodiesel from Dodonaea Plant Oil: Synthesis and Characterization-A Promising Nonedible Oil Source for Bioenergy Industry.

In this work, Dodonaea oil was studied as a potential biodiesel source. Dodonaea (Dodonaea viscosa Jacq.) is an evergreen shrubby plant that thrives in tropical and subtropical conditions. The plant produces high-grade biodiesel in terms of both quantity and quality despite its naturally high fat content. In the transesterification followed by esterification reaction, varied ratios of oil to methanol, constant temperature (60°), reaction duration (1 h), and different catalyst concentrations (0.25-0.75% (w/w) were utilized. A maximum biodiesel yield of 90% was achieved. For fuel characteristic analysis, the prepared biodiesel was specified and compared to ASTM criteria. The chemical composition was verified using analytical techniques such as FT-IR and NMR spectroscopy. As a result of the foregoing, Dodonaea is considered a possible bioenergy source, particularly in the transport sector.

Fault Tolerant DHT-Based Routing in MANET.

In Distributed Hash Table (DHT)-based Mobile Ad Hoc Networks (MANETs), a logical structured network (i.e., follows a tree, ring, chord, 3D, etc., structure) is built over the ad hoc physical topology in a distributed manner. The logical structures guide routing processes and eliminate flooding at the control and the data plans, thus making the system scalable. However, limited radio range, mobility, and lack of infrastructure introduce frequent and unpredictable changes to network topology, i.e., connectivity/dis-connectivity, node/link failure, network partition, and frequent merging. Moreover, every single change in the physical topology has an associated impact on the logical structured network and results in unevenly distributed and disrupted logical structures. This completely halts communication in the logical network, even physically connected nodes would not remain reachable due to disrupted logical structure, and unavailability of index information maintained at anchor nodes (ANs) in DHT networks. Therefore, distributed solutions are needed to tolerate faults in the logical network and provide end-to-end connectivity in such an adversarial environment. This paper defines the scope of the problem in the context of DHT networks and contributes a Fault-Tolerant DHT-based routing protocol (FTDN). FTDN, using a cross-layer design approach, investigates network dynamics in the physical network and adaptively makes arrangements to tolerate faults in the logically structured DHT network. In particular, FTDN ensures network availability (i.e., maintains connected and evenly distributed logical structures and ensures access to index information) in the face of failures and significantly improves performance. Analysis and simulation results show the effectiveness of the proposed solutions.

Green Recycling Supplier Selection of Shared Bicycles: Interval-Valued Pythagorean Fuzzy Hybrid Weighted Methods Based on Self-Confidence Level.

In the face of practical problems such as the increasing demand for shared bicycles and the number of faulty vehicles which are hard to handle and repair in time, shared bicycles operators tend to outsource recycling services to suppliers. To solve the problem of recycling supplier selection, this paper constructs a novel evaluation index system involving the three traditional dimensions and introduces an interval-valued Pythagorean fuzzy (IVPF) hybrid weighted decision-making model based on the self-confidence level. Subsequently, the self-confidence IVPF hybrid weighted average geometric operator and self-confidence IVPF ordered hybrid weighted average geometric operator are proposed by integrating the self-confidence level of experts, the superiority of the weighted and geometric average rules. The significant merit of the developed operators is that they can incorporate the self-confidence level of the expert as well as effectively combine the characteristics of the weighted and geometric average mechanism. A multi-attribute decision-making (MADM) framework is then constructed by using the proposed aggregation approach. Finally, on the basis of the established evaluation index system, a case concerning the green recycling supplier selection of shared bicycles is applied to display the superiority and practicability of the presented method.

Three-Dimensional Structure Characterization and Inhibition Study of Exfoliative Toxin D From Staphylococcus aureus.

The Staphylococcus aureus exfoliative toxins (ETs) are the main toxins that produce staphylococcal scalded skin syndrome (SSSS), an abscess skin disorder. The victims of the disease are usually newborns and kids, as well as grown-up people. Five ETs namely, exfoliative toxins A, B, C, D, and E have been identified in S. aureus. The three-dimensional (3D) structure of exfoliative toxins A, B, C and E is known, while that of exfoliative toxin D (ETD) is still unknown. In this work, we have predicted the 3D structure of ETD using protein modeling techniques (software used for 3D structure modeling comprising the MODELLER 9v19 program, SWISS-Model, and I-TESSER). The validation of the build model was done using PROCHECK (Ramachandran plot), ERRAT2, and Verify 3D programs. The results from 3D modeling show that the build model was of good quality as indicated by a GMQE score of 0.88 and by 91.1% amino acid residues in the most favored region of the Ramachandran plot, the ERRAT2 quality factor of 90.1%, and a verify3D score of >0.2 for 99.59% of amino acid residues. The 3D structure analysis indicates that the overall structure of ETD is similar to the chymotrypsin-like serine protease fold. The structure is composed of 13 ß-strands and seven α-helices that fold into two well-defined six-strand ß-barrels whose axes are roughly perpendicular to each other. The active site residues include histidine-97, aspartic acid-147, and serine-221. This represents the first structure report of ETD. Structural comparison with the other ETs shows some differences, particularly in the loop region, which also change the overall surface charge of these toxins. This may convey variable substrate specificity to these toxins. The inhibition of these toxins by natural (2S albumin and flocculating proteins from Moringa oleifera seeds) and synthetic inhibitors (suramin) was also carried out in this study. The results from docking indicate that the inhibitors bind near the C-terminal domain which may restrict the movement of this domain and may halt the access of the substrate to the active site of this enzyme. Molecular dynamic simulation was performed to see the effect of inhibitor binding to the enzyme. This work will further elucidate the structure-function relationship of this enzyme. The inhibition of this enzyme will lead to a new treatment for SSSS.

Two Promising Anti-Cancer Compounds, 2-Hydroxycinnaldehyde and 2- Benzoyloxycinnamaldehyde: Where do we stand?

Natural bioactive compounds with anti-carcinogenic activity are gaining tremendous interest in the field of oncology. Cinnamon, an aromatic condiment commonly used in tropical regions, appeared incredibly promising as an adjuvant for cancer therapy. Indeed, its whole or active parts (e.g., bark, leaf) exhibited significant anti-carcinogenic activity, which is mainly due to two cinnamaldehyde derivatives, namely 2-hydroxycinnaldehyde (HCA) and 2- benzoyloxycinnamaldehyde (BCA). In addition to their anti-cancer activity, HCA and BCA exert immunomodulatory, anti-platelets, and anti-inflammatory activities. The highly reactive α,ßunsaturated carbonyl pharmacophore, called Michael acceptor, contributes to their therapeutic effects. The molecular mechanisms underlying their anti-tumoral and anti-metastatic effects are miscellaneous, strongly suggesting that these compounds are multi-targeting compounds. Nevertheless, unravelling the exact molecular mechanisms of HCA and BCA remains a challenging matter which is necessary for optimal controlled-drug targeting delivery, safety, and efficiency. Eventually, their poor pharmacological properties (e.g., systemic bioavailability and solubility) represent a limitation and depend both on their administration route (e.g., per os, intravenously) and the nature of the formulation (e.g., free, smart nano-). This concise review focused on the potential of HCA and BCA as adjuvants in cancer. We describe their medicinal effects as well as provide an update about their molecular mechanisms reported either in-vitro, ex-vivo, or in animal models.