Rhipicephalus microplus ticks collected in Jingmen city  in 2010 is associated with febrile illness in humans. Since then, the geographic range has expanded to include Trinidad and Tobago, Brazil, and Uganda. However, the ecology of JMTV remains poorly described in Africa. We screened adult ticks  for JMTV infection by reverse transcription polymerase chain reaction (RT-PCR). Ticks were collected from cattle , goats , sheep , and free-ranging tortoises   in two Kenyan pastoralist-dominated areas (Baringo and Kajiado counties) with a history of undiagnosed febrile human illness. Surprisingly, ticks collected from goats  0.1–0.5), sheep , and tortoise  was also detected in blood from tortoises . Intragenetic distance of JMTV sequences originating from tortoise-associated ticks was greater than that of sheep-associated ticks. Phylogenetic analyses of seven complete-coding genome sequences generated from tortoise-associated ticks formed a monophyletic clade within JMTV strains from other countries. In summary, our findings confirm the circulation of JMTV in ticks in Kenya. Further epidemiological surveys are needed to assess the potential public health impact of JMTV in Kenya.Jingmen tick virus (JMTV) is an arbovirus with a multisegmented genome related to those of unsegmented flaviviruses. The virus first described in  Rhipicephalus microplus ticks in Jingmen city  in 2010 [Jingmen tick virus (JMTV) is an emerging human pathogen first described in  in 2010 . Variant in 2010 . In Finl in 2010 ,6,7. JMT in 2010 ,9. Howevflavivirus  and NS3, helicase/protease) [JMTV and related viruses have so far not been classified by the International Committee on Taxonomy of Viruses (ICTV) and are referred to as jingmenviruses ,11. Jingrotease) ,12. The To date, there is no information regarding the presence of JMTV infections in vertebrates or ticks in Kenya. Towards predictive surveillance for arboviral threats, this study sought to assess the presence and distribution of JMTV in adult ticks in Kenya. Ticks collected from livestock hosts such as cattle, goats, and sheep and free-ranging tortoises from two pastoralist-predominant areas, Baringo and Kajiado counties were assessed.All experimental procedures were approved by the Kenya Medical Research Institute Scientific and Ethics Review Unit (KEMRI-SERU) (SERU protocol number 3312). Local authorities and village elders were consulted before the study was initiated and during each sampling visit. Additionally, informed oral consent was obtained from owners and/or caretakers before sampling domestic animals. Tick sampling from livestock was performed in accordance with ethical guidelines.Adult ticks were collected from seven sites in two counties, Baringo and Kajiado, within the Great Rift Valley Region of Kenya. These counties  were selBos taurus), goats (Capra hircus), and sheep (Ovis aries), as well as from tortoises  in Baringo only, between August 2019 and July 2020 after the rains when arboviral activities are expected to be high [icipe in Nairobi. Following surface sterilization with 70% ethanol and washing with deionized water to remove foreign particles from animals, the collected ticks were identified morphologically to species using established morphologic keys [Adult ticks were collected from cattle   or approximately 50 µL whole blood spotted on FTA Classic Card Whatman . The samples on 2 mL BD Vacutainer were cryopreserved in liquid nitrogen for transportation while the samples on FTA cards were stored at room temperature during transportation. All blood samples were stored at −80 °C during transfer to the laboratory at Amblyomma ticks (that could not be identified at the species level by morphology) using the ISOLATE II Genomic DNA extraction kit . The supernatant was preserved at −80 °C for RNA extraction and virus isolation. Three PCR assays targeting the 16S ribosomal ribonucleic acid (rRNA), internal transcribed spacer 2 (ITS2), and cytochrome oxidase 1 (CO1) genes were employed for amplification  for 45 s in Mini-Beadbeater-16 . One mL DPBS  was added to each tick homogenate prior to centrifugation at 2500 revolutions per minute (rpm) at 4 °C for 10 min in a bench top centrifuge (Eppendorf 5430 R). Following the manufacturer’s protocol, genomic DNA was extracted from the pellet of fication  using thTotal RNA was extracted from 140 µL of tick homogenates (homogenization described above) and from tortoise whole blood using the QIAamp Viral RNA Mini Kit  following the manufacturer’s instructions. The tick homogenates included both samples homogenized in pools and those homogenized individually. The remaining homogenates were preserved at −80 °C for virus isolation. Reverse transcription was carried out with 5 µL of the isolated RNA using the High Capacity cDNA Reverse Transcription (RT) kit  and 600 μM non-ribosomal random primers . SamplesCeropithecus aethiops) and C6/36  cells as previously described following filtration and antibiotic treatment approaches [2 atmosphere at 37 °C while C6/36 cells were incubated at 28 °C without CO2. The cells were monitored regularly for cytopathic effects (CPE) and four blind passages on fresh cells were carried out after every seven days.Virus isolation attempts from JMTV-positive tick homogenates was performed in Vero E6  followed by cDNA synthesis using Superscript IV reverse transcriptase and random hexamer primers  as described by the manufacturer. A quantitative TaqMan Real-time PCR (qRT-PCR) using JMTV-specific primers and probe  was esta® RNA Virus Kit  following the manufacturer’s protocol. The extracted RNA was used to sequence JMTV full genomes on an Illumina MiSeq Next-generation sequencing (NGS) platform as described earlier with modification [http://jgi.doe.gov/data-and-tools/bb-tools/, accessed on 25 January 2022). The read coverage was then normalized, employing the kmer-based normalization toolBBNorm with a target option of 40 and minimum depth of 6. After trimming and normalization, the duplicate reads were binned using Dedupe. Viral sequence identification involved mapping paired reads against JMTV segments S1, S2, S3, and S4 as well as by de novo assembly using Spades v3.11.1 . Genome analysis was performed using Geneious Prime, and nucleotides (nt) and deduced amino acids (aa) sequences were queried against the GenBank database using blastn and blastx searches [Viral RNA was extracted from JMTV-positive tick homogenates using QIAamp Viral RNA Mini Kit  as described above without adding carrier RNA. Viral RNA was further extracted from infectious cell culture supernatant using the NucleoSpinfication  in that searches ,30.The partial sequences (ITS2 and 16S rRNA) for ticks and fragments of NS5 genes for JMTV were analyzed in Geneious Prime and queried in GenBank . Using thttp://www.cbs.dtu.dk/services/NetNGlyc/, accessed on 25 January 2022). JMTV phylogenetic trees were inferred from MAFFT alignment using PhyML v. 2.2.4 with General-time-reversible (GTR) substitution models employing 1000 bootstrap replicates. Trees were midpoint rooted.Full JMTV genomes were analyzed using Geneious prime . In summhttp://epitools.ausvet.com.au/, accessed on 4 November 2021) [The relative abundance of tick species collected from different hosts was estimated binomially and evaluated by Chi square tests at 95% confidence intervals using R version 4.1.2 . To estier 2021) ,35,36,37The ITS2 and 16S rRNA gene fragments sequences were deposited in GenBank under the accession numbers ON212401–ON212405 and ON220154–ON220159, respectively. The JMTV NS5 gene sequences were deposited in GenBank under the accession numbers ON158817–ON158867. JMTV coding complete genome sequences were deposited in GenBank under the accession numbers ON186499–ON186526 .Rhipicephalus (Rh.) appendiculatus, Rh. evertsi evertsi, Rh. pulchellus, Hyalomma(Hy.) marginatum, Hy. rufipes, Hy. truncatum, Hy. impeltatum, Hy. albiparmatum, Amblyomma(Am.) gemma, Am. nuttalli, Am. sparsum, Am. Variegatum and Am. lepidum  revealed that the Am. sp. ticks are most closely related to Am. marmoreum and Am. loculosum, showing pairwise nucleotide identities of 93%–94% to both species (Am. sp. ticks to Am. marmoreum (93%–94% nt similarity). These data suggest that the collected Am. sp. ticks are distinct from formally recognized Amblyomma tick species for which homologous 16S rRNA and ITS2 data are available  and Am. sp. , both collected from tortoises sampled in Kapkuikui (Baringo county), while Rh. appendiculatus  collected from sheep in Oloisinyai (Kajiado county) had the lowest prevalence (Rh. evertsi evertsi and Hy. truncatum (Pan-JMTV PCR and/or qRT-PCR screening of 718 tick pools (≤ 8 ticks/pool) yielded sixty-seven positive samples. Assuming only one positive tick per pool, this translates to an overall estimated individual-level JMTV prevalence of 1.5% . The highest individual-level JMTV prevalence was observed for evalence . Other pruncatum . Jingmenruncatum .Out of the sixty-seven JMTV-positive samples, fifty showed 93%–94% nt identity to JMTV detected in a non-human primate from Uganda (KX377513.1) in the NS5 gene  as shown in Rh. appendiculatus collected from sheep clustered together in a distinct monophyletic clade embedded in tortoise-tick-associated viruses, suggesting a tick and/or host specific clustering pattern . JMTV genome copies were detected in cell culture supernatants of seven samples following two cell culture passages. No cytopathic effects (CPE) were present. Cell culture supernatants comprised Rh. appendiculatus (KT125) collected from sheep, from Am. sparsum (MT293), and from Am. sp.  both collected from tortoise hosts. However, no virus replication was measured after the third passage in both Vero E6 and C6/36 cells. Multiple attempts to further passage the virus after two cell culture passages were not successful.Virus isolation was attempted using representative JMTV-positive samples (Am. sp. ticks (MT304 and MT299) inoculated into C6/36 and Vero E6 cells respectively, as well as from two Am. sparsum (MT290 and MT293) and three Am. sp.  homogenates. Each genome consisted of four genome segments and had a size of approximately 11 kb excluding the non-coding untranslated regions (UTRs). The genomes showed a typical segmented JMTV genome organization comprising three monocistronic segments  and two separate ORFs in segment 4  and Am. sp.  collected from tortoises in Kapkuikui. Interestingly, we did not find any tick collected from cattle positive for JMTV, although cattle from China have been shown to be infected with JMTV [JMTV was found in tick species that were not associated with JMTV before. Positive tick species included d Tobago ,39,40. OHyalomma ,41. The Am. gemma, which is also known to feed on humans and livestock and Am. falsomarmoreum [Am. sp. is not known, other tortoise-associated tick species reporting JMTV infection including Am. sparsum and Am. nuttalli have been shown to feed on livestock and humans, respectively [Integral to arbovirus disease transmission dynamics is the presence of a pathogen, a competent vector, and a susceptible animal host. In the frame of susceptible animal hosts inhabiting areas in Kenya with history of arboviral disease, tortoises are among widely distributed tick hosts. Tortoises are known to be long-lived reptiles and have low species richness, with only one or two species living in sympatry ,43. Commarmoreum ,47. In sarmoreum ,49. Screectively . OverallRh. microplus embryo-derived cell line) [Ixodes ricinus) cell lines [JMTV isolation attempts suggested only replication for two cell culture passages in Vero E6 and C6/36 cells. While the detection of JMTV RNA in cell culture supernatant may be an indication of virus replication in these cells, it is also possible that the JMTV RNA detections in cell culture supernatants were carryover from tick homogenates as speculated by Kobayashi et al. . Earlierll line) ,2,51. Otll lines ,53. In tSeven complete-coding genomes of JMTV were sequenced and characterized. A comprehensive analysis of coding regions showed a genome structure and functional organization comparable to those of other reported JMTVs. The RNA helicase in segment 3 was comparable to flavivirus NS3 helicase responsible for viral RNA capping and synthesis . The segOur findings showed circulation of JMTV in several tick species in Kenya. Virus-positive ticks were collected from sheep, goats, and tortoises, with the latter showing the highest JMTV infection rates. Interestingly, the diversity of tortoise-associated JMTV was much greater than that of sheep-associated JMTV. Further epidemiological surveys including antibody screening of livestock and humans are necessary to appraise the potential health risk posed by JMTV in the study areas and beyond.


Modern machine learning (ML) models are becoming increasingly popular and are widely used in decision-making systems. However, studies have shown critical issues of ML discrimination and unfairness, which hinder their adoption on high-stake applications. Recent research on fair classifiers has drawn significant attention to developing effective algorithms to achieve fairness and good classification performance. Despite the great success of these fairness-aware machine learning models, most of the existing models require sensitive attributes to pre-process the data, regularize the model learning or post-process the prediction to have fair predictions. However, sensitive attributes are often incomplete or even unavailable due to privacy, legal or regulation restrictions. Though we lack the sensitive attribute for training a fair model in the target domain, there might exist a similar domain that has sensitive attributes. Thus, it is important to exploit auxiliary information from a similar domain to help improve fair classification in the target domain. Therefore, in this paper, we study a novel problem of exploring domain adaptation for fair classification. We propose a new framework that can learn to adapt the sensitive attributes from a source domain for fair classification in the target domain. Extensive experiments on real-world datasets illustrate the effectiveness of the proposed model for fair classification, even when no sensitive attributes are available in the target domain. The recent development of machine learning models has been increasingly used for high-stake decision making such as filtering loan applicants  how to adapt the sensitive attributes to the target domain by transferring knowledge from the source domain; and (2) how to predict the labels accurately and satisfy fairness criteria. It is non-trivial since there are domain discrepancies across domains and no anchors are explicitly available for knowledge transfer. Our solutions to these challenges result in a novel framework called FairDA for fairness classification via domain adaptation. Our main contributions are summarized as follows:Therefore, we propose a dual-adversarial learning framework to via domain adaptation.We study a novel problem of fair classification airDA that simultaneously transfers knowledge to adapt sensitive attributes and learns a fair classifier in the target domain with a dual adversarial learning approach.We propose a new framework FWe conduct theoretical analysis demonstrating that fairness in the target domain can be achieved with estimated sensitive attributes derived from the source domain.We perform extensive experiments on real-world datasets to demonstrate the effectiveness of the proposed method for fair classification without sensitive attributes.In this section, we briefly review the related works on fairness machine learning and deep domain adaptation.Pre-processing approaches  = 𝔼, where Ŷ is predicted label. Demographic parity requires the behavior of the prediction model to be fair to different sensitive groups. Concretely, it requires that the positive rate across sensitive attributes are equal: 𝔼(Ŷ ∣ A = a) = 𝔼(Ŷ ∣ A = b), ∀a, b. The problem of fair classification with domain adaptation is formally defined as follows:We first introduce the notations of this paper, and then give the formal problem definition. Let Problem Statement: Given the training data In this section, we present the details of the proposed framework for fair classification with domain adaptation. As shown in fAθ that describes the modeling of predicting sensitive attributes and a domain classifier fdθ that illustrates the process of transferring knowledge to the target domain for estimating sensitive attributes. In addition, the adversarial debiasing module consists of a label predictor fYθ that models the label classification in the target domain, and a bias predictor faθ to illustrate the process of differentiating the estimated sensitive attributes from the target domain data.Specifically, first, the adversarial domain adaptation module contains a sensitive attribute predictor Since the sensitive attributes in the target domain are unknown, it is necessary to estimate the target sensitive attributes to build fair classifiers. Recent advancement in unsupervised domain adaptation has shown promising results to adapt a classifier on a source domain to the unlabeled data to the target domain  is to learn the representation for predicting sensitive attributes. To ensure that fAθ trained on fdθ to make the representation of source and target domains in the same feature space. Specifically, fdθ aims to differentiate if a representation is from the source or the target; while h1(·) aim to learn a domain-invariant representation that can fool fdθ, i.e.,Where d are the parameters of the domain classifier. The overall objective function for this module is a min-max game between the sensitive attributes predictor fAθ and the domain classifier fdθ as follows:Where θWhere α controls the importance of the adversarial learning of the domain classifier. To estimate the sensitive attributes in the target domain, we will utilize the following function: Â2 and the labels Y2 in the target domain. Specifically, we aim to learn a representation that can predict the labels accurately, while being irrelevant to sensitive attributes. To this end, we propose to feed the representation into a label predictor and a bias predictor. Specifically, the label predictor is to minimize the predicted errors of the labels with the following objective function:To learn a fair classifier for the target domain, we will leverage the derived sensitive attributes fYθ is to predict the labels, h2(·) is an embedding layer to encode the features into a latent representation space, and ℓ is a cross-entropy loss. Furthermore, to learn fair representations and make fair predictions in the target domain, we incorporate a bias predictor to predict the sensitive attributes; while h2(·) trying to learn the representation that can fool fYθ:Where a are the parameters for the adversary to predict sensitive attributes. Finally, the overall objective function of adversarial debiasing for fair classification is a min-max function:Where θWhere β controls the importance of the bias predictor.dual adversarial learning is as follows:We have introduced how we can estimate sensitive attributes by adversarial domain adaptation, and how to ensure fair classification with adversarial debiasing. We integrate the components together and the overall objective function of the fAθ to ensure a good estimation of Â2. Next, we will conduct a theoretical analysis of the dual adversarial learning for fairness guarantee.The parameters in the objective are learned through RMSProp, which is an adaptive learning rate method that divides the learning rate by an exponentially decaying average of squared gradients. We choose RMSProp as the optimizer because it is a popular and effective method to determine the learning rate abortively which is widely used for training adversarial neural networks  the adversarial domain adaptation for estimating sensitive attributes (Â2) of the first module.In this section, we perform a theoretical analysis of the fairness guarantee under the proposed framework Fsensitive attribute shift across two domains, i.e., the prior distribution changes as p(A1) ≠ p(A2). In addition, we assume that the other shifts are invariant across domains, for example, p(X1|A1) = p(X2|A2). Under the assumption of the sensitive attribute shift, we can derive the risk in the target domain as Kouw and Loog /p(A1) represents the change in the proportions in the sensitive attribute. Since we do not have samples with sensitive attributes from the target domain, we can use the samples drawn from the source distribution to estimate the target sensitive attributes distribution with mean matching  = p(Z2|Â2 = 0), where X2 according to the Proposition 1. in Goodfellow et al.  The estimated sensitive attributes p = p(Â2|A2)p(Z2|A2);(2) The estimated sensitive attributes are not random, i.e.,p(A2 = 1|Â2 = 1) ≠ p(|A2 = 0|Â2 = 1).fYθ will achieve demographic parity, i.e.,If p(Ŷ2|A2 = 0) = p(Ŷ2|A2 = 1).We first explain the two assumptions:h1(·) and h2(·) to predict the target sensitive attributes, and learn the latent presentation, it generally holds that Â2 is independent of the representation of X2, i.e., p = p(Â2|A2)p(Z2|A2);Since we use two separate embedding layers fAθ for sensitive attributes, it is reasonable to assume that it does not produce random prediction results.Since we are using adversarial learning to learn an effective estimator We prove Theorem 1 as follows:p = p(Â2|A2)p(Z2|A2), we have p = p(Z2|A2). In addition, when the algorithm converges, we have p(Z2|Â2 = 1) = p(Z2|Â2 = 0), which is equivalent with Since Based on the above equation, we can get,p(Z2|A2 = 1) = p(Z2|A2 = 0). Since p(Ŷ2|A2 = 1) = p(Ŷ2|A2 = 0), which is the demographic parity.Which shows that a global minimum achieves, i.e., airDA. We aim to answer the following research questions (RQs):In this section, we present the experiments to evaluate the effectiveness of FRQ1: Can FairDA obtain fair predictions without accessing sensitive attributes in the target domain?RQ2: How can we transfer fairness knowledge from the source domain while effectively using it to regularize the target's prediction?RQ3: How would different choices of the weights of the two adversarial components impact the performance of FairDA?We conduct experiments on four publicly available benchmark datasets for fair classification: COMPAS  and F1, and the fairness performance based on Demographic Parity and Equal Opportunity  = 𝔼(Ŷ|A = 0). We will report the difference of each sensitive group's demographic parity (ΔDP):Demographic Parity: A classifier is considered to be fair if the prediction Ŷ of positive instances is independent of the sensitive attributes. Concretely, it requires the true positive rates of different sensitive groups to be equal: 𝔼 = 𝔼. Similarly, in the experiments, we report the difference of each sensitive group's equal opportunity (ΔEO):Equal Opportunity: Equal opportunity considers one more condition than demographic parity. A classifier is said to be fair if the prediction Note that demographic parity and equal opportunity measure fairness performance in different ways, and the smaller the values are, the better the performance of fairness.RQ1, we compare the proposed framework with the aforementioned baselines in terms of prediction and fairness. All experiments are conducted 5 times and the average performances and standard deviations are reported in EO, ΔDP. We have the following observations:To answer airDA performs better in terms of both fairness metrics ΔDP and ΔEO across all six experiments.Adapting sensitive attribute information from a similar source domain could help achieve a better fairness performance in the target domain. For example, compared with ARL, KSMOTE and FairRF, which leverage the implicit sensitive information within the target domain, overall FairDA can achieve a better performance of fairness, while remains comparatively good prediction performance. For example, in Exp. 6 of CelebA dataset, the performance of ΔDP of FairDA increases 21.2% compared to Vanilla, on which no explicit fairness regularization applied, and the performance of ACC only drops 0.1%.In general, the proposed framework FairDA outperforms baselines consistently, which demonstrates the intuition of sensitive adaptation is effective and the proposed FairDA is robust.We conduct experiments on various source and target datasets. We observe that no matter whether the number of instances in the source domain is greater or smaller than the target one, the proposed FairDA framework. As shown in Section (4), FairDA contains two adversarial components. The first one is designed for making better predictions on target domain's sensitive attribute with the knowledge learned from the source domain. The second one is designed for debiasing with the sensitive attribute predicted by the domain adaptive classifier. In order to answer RQ2, we investigate the effects of these components by defining two variants of FairDA:In this section, we aim to analyse the effectiveness of each component in the proposed FFairDAw/o DA: This is a variant of FairDA without domain adversary on the source domain. It first trains a classifier with the source domain's sensitive attribute and directly applies it to predict the target domain's sensitive attribute.FairDAw/o Debiasing: This is a variant of FairDA without debiasing adversary on the target domain. In short, it is equivalent to Vanilla.airDA w/o DA), both ΔDP and ΔEO increase, which means the fairness performances are reduced. In addition, the classification performances also decline compared with FairDA. This suggests that the adaptation is able to make better estimations for the target sensitive attributes, which contributes to better fairness performances.When we eliminate the domain adversary for adapting the sensitive attributes information , there is no fairness regularization applied on the target domain. Therefore, it is equivalent to Vanilla. We could observe that the fairness performances drop significantly, which suggests that adding the debiasing adversary to FairDA is indispensable. In addition, even with the adversarial debiasing, FairDA can still achieve comparatively good F1 compared with FairDA w/o Debiasing. This enhances the intuition of leveraging adversary to debias.When we eliminate the debiasing adversary  for β, the fairness performance is consistently better with a higher value. From airDA can achieve relatively good performances of fairness and classification.To answer airDA using a dual adversarial learning approach to achieve a fair and accurate classification. We provide a theoretical analysis to demonstrate that we can learn a fair model prediction under mild assumptions. Experiments on real-world datasets show that the proposed approach can achieve a more fair performance compared to existing approaches by exploiting the information from a source domain, even without knowing the sensitive attributes in the target domain. For future work, first, we can consider multiple source domains available and explore how to exploit domain discrepancies across multiple domains to enhance the performance of the fair classifier in the target domain. Second, we will explore the fairness transfer under different types of domain shifts, such as the conditional shift of sensitive attributes. Third, we will explore other domain adaption approaches such as meta-transfer learning to achieve cross-domain fair classification.In this paper, we study a novel and challenging problem of exploiting domain adaptation for fair and accurate classification for a target domain without the availability of sensitive attributes. We propose a new framework FThe original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Flavobacterium sp. No. 92. Although most cyclomaltodextrinases have been classified in the subfamily GH13_20. This one has not been assigned any GH13 subfamily as yet. It possesses a non-specified immunoglobulin-like domain at its N-terminus mimicking a starch-binding domain (SBD) and the segment MPDLN in its fifth conserved sequence region (CSR) typical, however, for the subfamily GH13_36. The searches through sequence databases resulted in collecting a group of 108 homologs forming a convincing cluster in the evolutionary tree, well separated from all remaining GH13 subfamilies. The members of the newly proposed subfamily share a few exclusive sequence features, such as the “aromatic” end of the CSR-II consisting of two well-conserved tyrosines with either glycine, serine, or proline in the middle or a glutamic acid succeeding the catalytic proton donor in the CSR-III. Concerning the domain N of the representative cyclomaltodextrinase, docking trials with α-, β- and γ-cyclodextrins have indicated it may represent a new type of SBD. This new GH13 subfamily has been assigned the number GH13_46.In the CAZy database, the α-amylase family GH13 has already been divided into 45 subfamilies, with additional subfamilies still emerging. The presented in silico study was undertaken in an effort to propose a novel GH13 subfamily represented by the experimentally characterized cyclomaltodxtrinase from  Within the CAZy database sequence-based classification of glycoside hydrolases (GHs) , the fam8-barrel (TIM-barrel) as a catalytic domain employing the retaining reaction mechanism; (ii) the catalytic machinery consists of a catalytic nucleophile (aspartic acid), a proton donor (glutamic acid) and a transition-state stabilizer (aspartic acid) at the strands β4, β5 and β7, respectively; and (iii) sequences share from 4 up to 7 typical conserved sequence regions (CSRs). The canonical domain organization in the family GH13 consists of three domains: A , B (it protrudes out of the barrel in the place of the loop 3 connecting the strand β3 with the helix α3), and C , although various mainly starch-binding domains (SBDs) classified as a different carbohydrate-binding module (CBM) families being also found [The family GH13 can briefly be characterized by a few basic criteria as follows ,11,12,13so found .At the higher level of the CAZy hierarchy, the family GH13 has been grouped with related families GH70 and GH77 into the clan GH-H , whereasFlavobacterium sp. No. 92, whose three-dimensional structure was published already in 2003 [Bacteroides thetaiotaomicron [Zunongwangia profunda [Massilia timonae [Flavobacterium sp. No. 92 cyclomaltodextrinase, all the particular features of interest mentioned above.The present study has been undertaken in an effort to emphasize the relevancy of creating a novel GH13 subfamily around the cyclomaltodextrinase from  in 2003 . The enz in 2003  and subs in 2003 ,27,28. D in 2003 , this cy in 2003 . The rea in 2003 ,32,33,34 in 2003 ,23. Note in 2003 . Finallyaomicron , an α-amprofunda  and a cy timonae , which sFlavobacterium sp. No. 92 is an attractive subject worth deep in silico studies that should be helpful in elucidating its position within the entire α-amylase family GH13. Therefore, the aim of the present study has been to deliver the comprehensive results from such a bioinformatics analysis convincing enough in order to define a novel GH13 subfamily, the subfamily GH13_46, represented just by this unique cyclomaltodextrinase.All these attributes make thus the cyclomaltodextrinase from Flavobacterium sp. No. 92 [Bacteroides thetaiotaomicron [Zunongwangia profunda [Massilia timonae [http://www.cazy.org/, accessed on 29 October 2022), and they all share two specific features: (i) the intermediary character of the sequence in the fifth CSR—MPDxN [https://blast.ncbi.nlm.nih.gov/, accessed on 1 October 2020), using the amino acid sequence of the Flavobacterium cyclomaltodextrinase (UniProt Accession No.: Q8KKG0) as a query. In total, three searches with the same cyclomaltodextrinase query sequence were performed, i.e., separately limiting the searched databases to kingdoms of Bacteria, Archaea and Eucarya. With regard to sources of sequences caught by BLAST, one non-redundant amino acid sequence was selected to represent each species and/or bacterial strain. Furthermore, the simultaneous presence of three sequence-structural features was considered as basic criterium for sequence selection: (i) the N-terminal module homologous to that present in the cyclomaltodextrinase from Flavobacterium sp. No. 92 [The cyclomaltodextrinase from . No. 92 , neopullaomicron , α-amylaprofunda , and cyc timonae  were sel timonae ; http://SR—MPDxN ; and  up. No. 92  with a s. No. 92 ; and  six representatives of the most recently established subfamily GH13_45—three members grouped around the α-amylase BaqA from Bacillus aquimaris [Bacillus megaterium [In order to perform a convincing comparison covering the entire α-amylase family GH13, the selected set of the sequences forming the potential novel GH13 subfamily has been further completed by 145 sequences as follows : (i) thrquimaris ,20 and tgaterium . Sequenchttps://www.uniprot.org/, accessed on 26 November 2022) and/or GenBank  databases.All studied sequences were retrieved from the UniProt . The first three alignments were executed on 108 Flavobacterium cyclomaltodextrinase-like sequences (that should define the new GH13 subfamily), whereas the fourth alignment was done with the full set of 253 sequences . While the former alignments (108 sequences) were based on: (i) N-terminal modules; (ii) the GH13 canonical part of the enzymes ; and (iii) the full-length enzymes; the latter alignment (253 sequences) was based on the substantial part of the catalytic domain spanning the sequence segment from beginning of the CSR-VI (strand β2) to the end of the CSRV-VII (strand β8) including the domain B. Information about the domain boundaries and all CSRs of individual sequences was obtained from the literature describing the sequences of biochemically characterized members of the individual subfamilies and previous in silico studies [Four different sequence alignments were performed using the program Clustal-Omega . For the trees of the newly proposed GH13 subfamily, the branch swap filter parameter has been set to “very strong,” and all other specifications were used in a default mode. Finally, all four calculated tree files were displayed with the program iTOL .Four evolutionary trees were calculated for the four above-mentioned sequence alignments. All were calculated as maximum-likelihood trees  using the WAG substitution model  and the am iTOL .The sequence logo of seven well-established CSRs for all 108 sequences of the potentially novel GH13 subfamily represented by the cyclomaltodextrinase from  server  for (i) cyclomaltodextrinase from Flavobacterium sp. No. 92 .Three-dimensional structures were retrieved from the Protein Data Bank .The full-length tertiary structure of the cyclomaltodextrinase from . No. 92  was used. No. 92  was comp. No. 92  as well x orenii . All terx orenii ; http://Flavobacterium sp. No. 92 may eventually function as an SBD. The docking trials using the program AutoDock and MGL Tools v1.5.6 [https://pubchem.ncbi.nlm.nih.gov/, accessed on 30 September 2021) and converted into PDB coordinates by the SMILES program . The resulting complexes of individual structures with bound cyclodextrins were displayed using the UCSF Chimera program [In order to inspect whether or not the N-terminal domain of the cyclomaltodextrinase from s v1.5.6  were pers v1.5.6 ; PDB cods v1.5.6 ; https:/program  neaomicron ; (iii) αprofunda ; and , which is a microscopic single-celled flagellated protozoan parasite [Bacteroides thetaiotaomicron [Euryarchaeota archaeon (UniProt: A0A2E0K4E8), it has been placed in the largest cluster where the Flavobacterium sp. No. 92 cyclomaltodextrinase [In order to follow the evolutionary relationships within the new GH13 subfamily, the evolutionary tree based on the alignment of complete sequences was calculated . Since oparasite , has beeaomicron . With rextrinase  is foundFor comparison, two further corresponding evolutionary trees were constructed: (i) based on the alignment of family GH13 canonical domains A, B, and C, i.e., excluding the domain N ; and ii. It is wTritrichomonas foetus , which can provide possible stacking interactions  the N-terminal domain not compatible with the SBD of the family CBM34  that is typically from the CAZy subfamily GH13_20  and is nly CBM34  present ly CBM34 , for whiaomicron , the α-aprofunda  and the  timonae  but alsoWith regard to relationships within the new subfamily, three evolutionary trees have been constructed based on the alignment of (i) complete sequences ; (ii) seFlavobacterium sp. No. 92 may strongly be supported by a comparison of all seven CSRs (The proposal to establish a novel GH13 subfamily around the cyclomaltodextrinase from ven CSRs  characteven CSRs  in the even CSRs . The treven CSRs . First, ven CSRs . The comven CSRs a that, iven CSRs , containven CSRs b.Flavobacterium sp. No. 92 [Flavobacterium sp. No. 92 cyclomaltodextrinase shares no exceptionally high level of structural similarity with any GH13 subfamily. This fact also supports the independence of the entire group it represents as a novel subfamily.As far as the structural comparison of the full-length cyclomaltodextrinase from . No. 92  with its. No. 92 ,30 could. No. 92 ,76,77,78Flavobacterium sp. No. 92, nor the tertiary structures solved to date have been determined with any α-glucan bound to the domain N [Halothermothrix orenii (In the following part of the structural analysis of the cyclomaltodextrinase, attention was aimed at its N-domain itself. The results from the pair-wise comparisons of this domain with representatives of all 14 relevant SBD CBM families [domain N ,29. It, domain N  typical x orenii . Again, Flavobacterium sp. No. 92. A similar CBM-like domain of amylomaltases from Escherichia coli [Corynebacterium glutamicum [The presented in silico experiments were finally completed by docking trials performed in an effort to demonstrate the eventual binding of α-glucans by the N-terminal domain of the cyclomaltodextrinase from hia coli  and Coryutamicum  from theutamicum . Here, futamicum . AlthougFlavobacterium sp. No. 92 definitively deserves the creation of its own new subfamily within the α-amylase family GH13, the subfamily GH13_46.In any case, based on the present study, the entire group of amylolytic enzymes and hypothetical proteins represented by the cyclomaltodextrinase from


The structural and functional properties of physical modified rice flour, including ultrasound treated rice flour (US), microwave treated rice flour (MW) and hydrothermal treated rice flour (HT) were investigated with wet-milled rice flour (WF) used as a positive control. The results showed the presence of small dents and pores on the rice flour granules of US and MW while more fragments and cracks were showed in HT. XRD and FTIR revealed that moderate ultrasonic treatment promoted the orderly arrangement of starch while hydrothermal treatment destroyed the crystalline structure of rice flour. In addition, the significant decrease of gelatinization enthalpy and the narrowing gelatinization temperature were observed in US. Compared to that of SF, adding physical modified rice flour led to a batter with higher viscoelasticity and lower tan δ. However, the batter added HT exhibited highest G′ and G″ values and lowest tan δ, which led to a harder texture of bread. Texture analysis demonstrated that physical modified rice flour (except HT) reduced the hardness, cohesion, and gumminess of rice bread. Especially, the specific volume of bread with US increased by 15.6% and the hardness decreased by 17.6%. This study suggested that ultrasound treatment of rice flour could improve texture properties and appearance of rice bread. Due to the increase in the prevalence of gluten-related diseases, such as celiac disease, gluten-free bread has a growing demand and consumption . Rice flw/w) within a certain temperature range, which would destroy the crystallization structure of starch and change the solubility, viscosity and expansion ability of rice flour. Ruiz, Srikaeo and Revilla [Studies have shown that hydrothermal treatment, microwave and ultrasound are commonly used as physical modifications. Hydrothermal treatment is based on treating materials with moisture content less than 35%  represents the strengths of the intermolecular hydrogen bonds in rice flour, and is presented in The absorption peak of -OH (3200–1600 cm−1) was estimated from the relative area of each individual peak shown in In order to explore the effect of physical modification on the protein secondary structure, the change in amide I (1700p > 0.05) and lower than (p < 0.05) that of modified rice flour. In contrast, WAI, WS and SP of HT was highest in all samples. The higher hydration properties values could be due to the highest DS content and the cracks and fragments of the damaged granules, which made the granules easier to absorb water and expand [Water absorption index (WAI), water solubility (WS) and swelling power (SP) of rice flour with different physical modifications are shown in d expand . In addid expand . Ultrasop > 0.05) changes were observed in the value of gelatinization temperature and ΔH of MW. Nevertheless, the ΔH of US presented a decreased trend, which might be related to the higher DS content and the weakening of amorphous regions. The pores and cracks on the surface of DS  provided by Panjin Pengyue Rice Industry Co., Ltd. was used in this study. The moisture content was 11.46%, protein: 8.21% dry basis (db), total starch: 80.75% db and amylose: 18.80% db, respectively. Semidry-milled rice flour (SF) was prepared according to Qin et al. . A totalWet-milled rice flour (WF) was prepared as follow: 200 g of polished rice grains were soaked in 400 mL water for 2 h and then milled in a colloid mill . The obtained slurry was freeze-dried  and then sifted through a 100-mesh screen. In this study, SF and WF were set as the control.w/v) and stirred for 10 min to obtain a homogeneous slurry. An ultrasonic processer  equipped with a 6 mm titanium alloy probe was used. According to the method of Yang et al. (2019) [SF was suspended in distilled water to give a concentration of 30% (. (2019)  with minA 100 g of SF was put in a glass container and then placed in the center of the microwave oven . As per the previous method with slight modifications , samplesw/w) suspension and stirred continuously in a hot water bath until the inner temperature reached 65 °C. The rice slurry was heated in a hot water bath for 30 min. Then, the paste was cooled at room temperature and freeze-dried. The dried rice was milled into flour by a grinder and passed through a 100-mesh screen. The sample was stored in a desiccator at room temperature.Hydrothermally treated rice flour (HT) was prepared by referring to the method of Bourekoua et al.  with minThe particle size of all samples was determined by Malvern MasterSizer 3000 . In addition, D50 (the particle diameters at cumulative volume percentage of 50%) was calculated by the software provided by the device. The DS content (AACC Method 76–31.01) was measured by commercial assay kit .Rice flour was fixed onto the surface of a circular aluminum stud with double-sided sticky tape and then observed using a scanning electron microscopy  under 10 kV.The crystallization characteristics of freeze-dried rice flour were determined by X-ray powder diffractometer . Scans were performed at diffraction angles (2θ) ranging from 5° to 45°, with a scanning rate of 10°/min and step size of 0.02°. Then, 40 kV and 40 mA with Cu-Kα radiation were set as operating conditions. The relative crystallinity (%) of all samples was calculated by MDI Jade 6.0 software .g for 30 min. Subsequently, the sediment was weighed for calculating WAI. The supernatants were collected in an aluminum dish of a known weight, dried at 105 °C until the weight was constant [Water hydration property included water absorption index (WAI), water solubility (WS) and swelling power (SP). Additionally, 100 mg of rice flour was dispersed in 10 mL distilled water and stirred for 30 min at 25 °C. The suspensions were then cooled to room temperature and centrifuged at 8500× constant . WAI, WSconstant .w/w), followed by grounding and pressing into tablets. The wavenumber range was set in the range of 4000–600 cm−1 at a resolution of 4 cm−1 with 64 scans. The spectrum was normalized by using OMNIC . The changes in the short-range order structure of starch were calculated by the absorbance ratio 1047/1022 (R1047/1022). Amide I bands (1700–1600 cm−1) were analyzed using PeakFit 4.12 .The FTIR spectra of rice flour samples were obtained using the FTIR spectrometer . Samples were equilibrated at 45 °C for 24 h and mixed with KBr . The sealed samples were balanced overnight at 4 °C and scanned at a temperature range of 30–110 °C at a rate of 10 °C/min. A sealed empty pan was used as a reference [The thermal characteristics of physical modified rice flour were measured by a DSC8000 analyzer . Then, 3 mg of rice flour was accurately weighed in an aluminum pan, and deionized water was added at a ratio of 1:2  was adopted to measure the pasting properties of the samples. Each sample  was mixed with 25 g distilled water before being transferred into an aluminum canister. The sample was equilibrated at 50 °C for 1 min, heated from 50 °C to 95 °C at 0.2 °C/s, held for 2.5 min at 95 °C, then cooled to 50 °C at the rate of 0.2 °C/s, and finally maintained at 50 °C for 2 min .–100 rad/s with 0.01% strain [The dynamic viscoelasticity of rice batter  were assessed by a Rheometer . The resting time of batter samples before the measurement was 5 min. Dynamic viscoelasticity measurements were done using parallel plate geometry  at 25 °C. Conduct frequency scanning of 0.1% strain . Three r–30 °C to hydrate. The other dry ingredients were mixed evenly for 5 min using a Pin Mixer . Then, the hydrated yeast mixture and batter were added and mixed for 5 min. After stirring, 50 g of batter was filled in a baking tray (70 mm × 70 mm × 40 mm) and proofed in a fermentation chamber  for 40 min at 38 °C and 85% relative humidity. The batter was put in an electric oven  and the baking parameters were set at 150 °C for 15 min. After baking, the bread was taken out and then cooled for 1 h. Finally, the samples were sealed and stored for determination. Bread was made three times for each formulation.The physical modified rice flour of US, MW and HT were prepared into bread, and mixed with SF in the ratio of 3:17 . The gluten-free rice bread formula was based on 100 g mixed rice flour, 90 g water, 4 g HPMC, 20 g sugar, 10 g batter and 2 g yeast. Yeast was first dissolved in water at 28Bread volume (mL) was measured after 1 h cooling and determined by the rapeseed displacement method 10-05 . The specific volume (mL/g) was calculated as the volume divided by the weight measured 1 h after baking.g with 10 kV.After baking and cooling, the breadcrumbs were immediately frozen by liquid nitrogen and then freeze-dried. The size of 4 mm × 2 mm × 2 mm small pieces were cut from the center of the breadcrumbs, and then their microstructures were examined by SEM at magnifications 1000× Crumb texture was determined by using a Texture Analyzer . Small piece sizes of 15 mm × 15 mm × 15 mm were cut from the center of the breadcrumbs. The texture profile analysis (TPA) double compression test was performed by an aluminum probe , which could penetrate 50% depth at 1 mm/s speed test with a 5 s delay between the first and second compression. The trigger force was 5 g. A total of 12 replicates were carried out.Rice flour was subjected to ultrasound, microwave and hydrothermal treatments. These physical modified treatments significantly changed the particle size and structure of rice flour, which affected their hydration, pasting and rheological behavior, and further changed the rice bread quality. After hydrothermal treatment, the structure of starch granules was seriously destroyed, and the percentage of irregular curl in the protein secondary structure increased. The excessive batter viscoelasticity of HT limited the development of the batter during fermentation, resulting in a stiffer bread crumb and smaller bread volume. In addition, microwave treatment weakened the hydrogen bonding force and changed the secondary structure of the protein with the conversion from β-turn to β-sheet. The doughs made with MW showed higher viscoelasticity and more stable cell structure than that of SF. Especially, the starch structure of US was reinforced and the protein secondary structure was modified with the decrease in β-turn and increase in α-helix. These molecular changes could explain the decrease of the pasting profile and narrowing of the gelatinization range in US. Moreover, the viscoelasticity of the batter containing 15% US was significantly improved compared to the SF batter, leading to a higher bread volume and softer crumb texture close to those of bread with WF. In conclusion, ultrasound modification is an alternative to improve the morphology and physical properties of rice flour and further improve gluten-free bread quality.


The influence of the domain structure’s initial topology and its evolution on the hysteresis curves of tetragonal and rhombohedral polydomain structures of ferroelectroelastic materials is studied. Based on the analysis of electrical and mechanical compatibility conditions, all possible variants of representative volume elements of tetragonal and rhombohedral second-rank-domain laminate structures were obtained and used in simulations. Considerable local inhomogeneity of stress and electric fields within the representative volume, as well as domain interaction, necessitates the use of numerical methods. Hysteresis curves for laminated domain patterns of the second rank were obtained using finite-element homogenization. The vector-potential finite-element formulation as the most effective method was used for solving nonlinear coupled boundary value problems of ferroelectroelasticity. A significant anisotropy of the hysteresis properties of domain structures was established both within individual phases and when comparing the tetragonal and rhombohedral phases. The proposed approach describes the effects of domain hardening and unloading nonlinearity. Due to remarkable material properties, such as strong intrinsic electromechanical coupling, the remanent polarization ability, and high dielectric permittivity, ferroelectric/ferroelastic materials are increasingly preferred in industrial and scientific applications. Ferroelectric ceramics are widely used as actuators and sensor applications ,2,3,4,5,single crystals have begun to demonstrate an advantage in comparison with commonly used polycrystalline ferroelectrics in achieved actuation strain and polarization levels along with reduced coercive field and enhanced piezoelectric coupling  :(44)[Bu]The divergence of the vector potential is approximated by the relationship The FE equations follow on from the substitution of constitutive relationships (34) and Equations (42)–(44) into the variational principle (41):The micromechanical models of the ferroelectroelastic behavior of materials  and the The formulation of the initial-boundary value problem for the RVE of an isothermal ferroelectroelastic multidomain crystal includes physical equations in the volume periodic boundary conditions are the most accurate. Assuming that the displacement vector For strictly periodic RVE, the S that is designated as For RVEs with a boundary Using the periodic boundary conditions (50) satisfies Hill’s homogeneity conditions.x is along [100]) of the electric vector potential is presented in the RVE. A constant value is required on side IV and equal to zero on side III . If there is a 180-degree wall, but it is a rank-2 wall that can be found from the second pair of indices  and electromechanical hysteresis (von Mises strain intensity vs. electric field) for the rhombohedral R{1221} topology are presented in Dielectric and electromechanical hysteresis curves for the 001] see a. This c001] see b.The residual field distribution inside RVE T{1221} for the von Mises micro-stress intensity, axial remanent polarization, and von Mises plastic strain intensity are shown in The polarization and electric field in Even though RVEs of tetragonal and rhombohedral topologies studied in this section are geometrically identical, they demonstrate significant differences in hysteresis behavior and internal residual field structures.Thus, it can be concluded from the numerical simulations that the rank-2 laminate domain structure of rhombohedral ferroelectrics exhibits a lower level of anisotropy due to the structure of initial spontaneous polarization. On the other hand, correctly oriented tetragonal laminate domain patterns can present larger magnitudes of polarization both in saturated and remnant (unloaded after saturation) states.The results of the finite-element modeling and simulation of the rank-2 laminate tetragonal and rhombohedral domain structure evolution of ferroelectroelastic materials were obtained and discussed. Based on the analysis of electrical and mechanical compatibility conditions, 14 unique domain topologies for the rhombohedral phase and 8 unique domain topologies for the tetragonal phase were obtained.The vector-potential finite-element formulation was used for solving nonlinear coupled boundary value problems of ferroelectroelasticity. The convergence of the global iterative procedure of the Newton–Raphson method takes place for all considered RVEs of ferroelectric multidomain structures.Considerable local inhomogeneity of stress and electric fields within the representative volume were observed. Hysteresis curves for laminated rank-2 domain patterns were obtained using finite-element homogenization.The influence of phase and topology is studied via a series of computations for the RVE of ferroelectrics rank-2 laminate multidomain structures under the loading with a cyclic electric field. For the considered loading directions, rhombohedral-phase RVEs were found to show less anisotropy in hysteresis behavior than tetragonal. The latter were found to have one or two preferable directions of loading corresponding to lattice edges and respective spontaneous polarization directions. The proposed approach describes the effects of domain hardening and its sensitivity to phase, domain structure, and loading direction.


Cyclin-dependent kinases 5 (Cdk5) is a special member of proline-directed serine threonine kinase family. Unlike other Cdks, Cdk5 is not directly involved in cell cycle regulation but plays important roles in nervous system functions. Under physiological conditions, the activity of Cdk5 is tightly controlled by p35 or p39, which are specific activators of Cdk5 and highly expressed in post-mitotic neurons. However, they will be cleaved into the corresponding truncated forms namely p25 and p29 under pathological conditions, such as neurodegenerative diseases and neurotoxic insults. The binding to truncated co-activators results in aberrant Cdk5 activity and contributes to the initiation and progression of multiple neurological disorders through affecting the down-stream targets. Although Cdk5 kinase activity is mainly regulated through combining with co-activators, it is not the only way. Post-translational modifications of Cdk5 including phosphorylation, S-nitrosylation, sumoylation, and acetylation can also affect its kinase activity and then participate in physiological and pathological processes of nervous system. In this review, we focus on the regulatory mechanisms of Cdk5 and its roles in a series of common neurological disorders such as neurodegenerative diseases, stroke, anxiety/depression, pathological pain and epilepsy. Cyclin-dependent kinases (Cdks) are a group of small proline-directed serine/threonine kinases mainly involved in the modulation of cell cycle, gene transcription and cell differentiation . Cyclin In the developing nervous system, Cdk5 seems to be expressed mainly in terminally differentiated neurons but not proliferating cells. Because the expression and kinase activity of Cdk5 was shown to increase progressively from embryonic day 15 (E15) and reaches the peak at E17 in developing mouse forebrain, which period is a critical time widow for neuronal differentiation . During As for p35, the co-activator of Cdk5, its expression becomes detectable in E16 rat brains and gradually increases to its peak level at P7–P14, then declines in the adult and aged rat brains. The Cdk5 kinase activity is low at E12 and it also progressively reaches a peak between P7 and P14, and then declines from 1 to 3 M, a timetable correlating well with the expression pattern of p35 . DiffereCyclin-dependent kinases 5 complex plays a very important role in neuronal functions from embryogenesis to postnatal brain modulation. During embryogenesis, Cdk5 is essential for normal brain development and conditional deletion of Cdk5 is lethal . It is b2+ activated protease, is involved in multiple physiological processes and plays an important role in maintaining normal neuronal function. The activation of calpain depends on Ca2+ concentration, which makes it vulnerable to changes of Ca2+ homeostasis  83 and 157 contributed to the elevation of Cdk5 kinase activity , 2012. Tin vivo . The cysin vivo .Sumoylation and acetylation are two other ways of post-translational modifications of Cdk5 activity. It has been shown that p35 is a novel sumoylation target and the sumoylation of p35 can enhance the activity of Cdk5/p35 complex . HoweverParkinson’s disease (PD) is a common neurodegenerative movement disorder characterized by widespread degeneration of dopaminergic neurons located in the substantia nigra pars compacta (SNpc) and subsequent loss of dopamine reaching striatal projecting neurons . The forin vitro and in vivo, decreased its solubility, induced its accumulation and subsequently reduced E3 ubiquitin-ligase activity  and then assembled into ring-like structures wrapping around MOM. Following GTP hydrolysis, Drp1 incises the membrane and instigates mitochondrial fission . In non-activity . Consistactivity . Glycopractivity .Mitochondrial dysfunction and aggregation of damaged mitochondria can cause remarkable oxidative stress indicating by excessive accumulation of cellular reactive oxygen species (ROS). Peroxidases are a series of antioxidant enzymes with the capacity to catalyze hydrogen peroxide into stable non-toxic molecules. Cdk5 was demonstrated to phosphorylate peroxidases 2 (Prx2) at Thr89 and this phosphorylation decreased its peroxidase activity and induced ROS over-generation and dopaminergic neuron loss in the SNc following MPTP insult . IncreasExcessive autophagy is closely related with neuronal death and there is over-production of autophagy markers in PD brains . KnockdoThe pathways related with Cdk5 in PD are summarized and presented as Alzheimer’s disease (AD) is the primary reason for dementia among people over the age of 65. It has two main pathological characteristics, one is senile plaques mainly composed by amyloid-β (Aβ) peptides which is resulted from aberrant amyloid precursor protein (APP) cleavage, and the other is neurofibrillary tangles (NFTs) basically consisting of paired helical filaments (PHFs) which are derived from hyperphosphorylated tau proteins . These tvia signal transducer and activator of transcription 3 (STAT3), who binded to BACE1 promoter and phosphorylated it at Ser727. In cultured primary rat hippocampal neurons, Cdk5 activation triggered peroxisome proliferators-activated receptor γ (PPARγ) phosphorylation at Ser273, then increased BACE1 activity and Aβ production  and γ-secretase. Aβ40 and Aβ42 are two main forms of Aβ peptide, the longer Aβ42 has a much stronger tendency to oligomerize and aggregate than the shorter Aβ40, and exhibits more neurotoxic effect. Accumulation of oligomerized Aβ peptides forms amyloid plaques, which is closely related with neuronal loss and cognitive decline in AD. Cdk5/p25 activity was upregulated and significantly correlated with BACE1 elevation in brains of AD patients and transgenic mouse models . Wen et oduction . Presenioduction . As the oduction . Cdk5/p3oduction , and theTau is a microtubule-associated protein primarily distributed in axons. Tauopathy is characterized by abnormal tau aggregation and NFT formation in the brain, which is a hallmark of AD. Cdk5/p25 can promote tau dimerization through phosphorylating it at different sites, which subsequently aggregate into PHF-like filament, resulting in microtubule collapse and neurite retraction . The CdkBesides the above-mentioned Aβ generation and NFT formation, CNS inflammation caused by microglia activation is another main feature of AD, which correlates with the plaque accumulation and may exacerbate the pathology of AD . Aβ olig2+ level elevation, which in turn lead to even higher Cdk5 activity, then shapes a vicious circle and contributes to neuron loss in AD  is a progressive neurodegenerative disease characterized by chorea, personality changes and dementia . It is mIt has been demonstrated that htt co-localized with Cdk5 in cellular membrane . Cdk5 coPhosphorylation of huntingtin at Ser421 has been shown to be neuroprotective against intrastriatal QA injection . In contThese findings suggest the multifaceted roles of Cdk5 in HD. Future studies are still needed to further clarify the relationship between Cdk5 dysfunction and HD pathogenesis.Stoke is an acute neurologic event caused by dramatic reduction of cerebral blood flow to a localized part of brain . Accordiin vivo both induced the cleavage of p35 into p25  contributed to a variety of neurological diseases including stroke. Phosphorylation of NMDAR subunits at the cytoplasmic carboxyl termini is an important way to regulate NMDAR function. It has been shown that Cdk5 can phosphorylate NMDAR at multiple sites. The phosphorylation of GluN2A at Ser1232 by Cdk5 enhanced receptor function and promoted CA1 pyramidal neuron death following transient forebrain ischemia  mice compared with control mice following chronic unpredictable stress, correlating with reduced depressive-like and anxiety-like behaviors (There are multiple mechanisms involved in the regulation of anxiety/depression by Cdk5. The dysfunction of glucocorticoid receptor (GR) signaling critically contributed to the pathology of psychiatric disorders. Cdk5 was shown to phosphorylate GR at serine 232 and there was a significant correlation between elevated Cdk5 activity and enhanced GR phosphorylation in hippocampus and PFC of the depressive rats . The mecehaviors . Depressehaviors . Anomaloehaviors . Optogenehaviors .Acute nociceptive pain is the physiological sensation of injury that helps animals survive by promoting them to withdrawal from the harmful stimuli and avoid further contacting with such stimuli. However, pathological and chronic pain seems meaningless and will cause much distress. Allodynia and hyperalgesia are two kinds of behavioral phenotypes indicated by decreased threshold or amplification in the responsiveness to noxious stimulation following chronic pain . Mountintrans-activators. Subsequently, Egr-1 binds to the promoter region of p35 and increases Cdk5 activity  is fast activated in response to innocuous and noxious stimulation . The levactivity . These rin vitro. The conditional TGF-β1 knockout reduced Cdk5 activity and Cdk5-dependent TRPV1 phosphorylation with attenuation of thermal hyperalgesia in mice following inflammatory pain  is mainly expressed in the nociceptive sensory neurons and potentiate pain sensitization in different pain models . The phoory pain . TNF-α wory pain . These rory pain . Cdk5 isory pain . Inhibitory pain .Besides its involvement in inflammatory pain, Cdk5 has been also shown to modulate several other kinds of pain such as neuropathic pain , bone caEpilepsy affects over 70 million people worldwide, which is mainly manifested by recurrent seizures and brings a variety of physiological and psychosocial consequences . The levvia p38 MAPK inhibition in rat frontoparietal cortex (Sustained endoplasmic reticulum (ER) stress triggers the regional specific astroglial responses, which contributed to the status epilepticus (SE). Cdk5 phosphorylation was shown to be upregulated in the astrocytes within the hippocampus CA1 region and dentate gyrus following ER stress. Inhibition of Cdk5 with roscovitine markedly suppressed hippocampal astroglial response induced by ER stress , which ml cortex . Blood–bl cortex .As one up-stream kinase in the nervous system, Cdk5 triggers the down-stream signaling pathways through interacting with its substrates. Numerous Cdk5 substrates have been detected and their abnormal alterations following aberrant Cdk5 activity are closely related with initiation and progression of neurological disorders. In this review, some important substrates of Cdk5 are listed in As a kinase distributed extensively in the nervous system, Cdk5 plays crucial roles in various kinds of neuronal function. Aberrant activation of Cdk5 appears to be a driving force for the initiation and progression of multiple neurological disorders. Numerous molecular targets and pharmacological mechanisms are involved in the Cdk5-mediated neurodysfunction . The extAs the aberrant Cdk5 activity is generally caused by p25 accumulation, so small molecule protein-protein interaction (PPI) inhibitors targeted to disturb the interactions between Cdk5 and p25 may represent a promising strategy. It can not only eliminate Cdk5/p25 complex-induced hyper-activation but also retain the physiological function of Cdk5/p35. In addition, there is no concern about the selectivity, as the inhibitors are developed to target the specific PPI site of Cdk5 and p25 without affecting other Cdks kinase activity. However, it can be predicted that the development of any kind of drugs, including the small molecule PPI inhibitors, will not always be smooth. But it may shed light upon the treatment of Cdk5-related neurological diseases. Future extensive studies are still needed to define more precisely the role of Cdk5 hyperactivation in brain function impairments, and it will facilitate the discovery of more effective therapeutic strategies targeting Cdk5 aberrant activity implicated in neurological disorders.ZT and JT designed the review. JT and X-QW searched the literature. ZT and BF made the figures and table. ZT, X-QW, BF, and JT wrote and edited the original draft. All authors have read and agreed to the published version of the manuscript.


S-adenosylmethionine (rSAM) enzymes have become popular targets for electron paramagnetic resonance (EPR) spectroscopic studies. In contrast to prototypic single-domain and thus single-[4Fe–4S]-containing rSAM enzymes, there is a large subfamily of rSAM enzymes with multiple domains and one or two additional iron–sulfur cluster(s) called the SPASM/twitch domain-containing rSAM enzymes. EPR spectroscopy is a powerful tool that allows for the observation of the iron–sulfur clusters as well as potentially trappable paramagnetic reaction intermediates. Here, we review continuous-wave and pulse EPR spectroscopic studies of SPASM/twitch domain-containing rSAM enzymes. Among these enzymes, we will review in greater depth four well-studied enzymes, BtrN, MoaA, PqqE, and SuiB. Towards establishing a functional consensus of the additional architecture in these enzymes, we describe the commonalities between these enzymes as observed by EPR spectroscopy.Owing to their importance, diversity and abundance of generated paramagnetic species, radical  S-adenosylmethionine (rSAM) enzyme superfamily is the largest known, with most of its members currently uncharacterized  cluster .MoaA is another twitch domain-containing rSAM enzyme which catalyzes the cyclization of GTP to 3′,8-cH14/15 N and the paramagnetic Aux cluster  cluster through either or both the guanosine N1 and the amine N2 . However cluster . The aut2H]GTP with non-labeled SAM, suggesting that H3′ of GTP is abstracted by 5′-dA• to initiate the reaction. In addition, using various SAM isotopologues also affected the EPR splitting pattern and thus the line shape, further confirming that the intermediate is indeed a SAM-based radical, rather than a GTP-based radical  and [2Fe–2S] AuxI clusters were discussed in a subsequent publication, such as a higher abundance of [2Fe–2S] in aerobes and facultative anaerobes + AuxI signal is present  via a two-electron oxidation Fig. A in the naerobes . MoreoveAuxI 2.10 could beg-tensors were well resolved by X-band (9.4 GHz) spectra, Q-band (34.0 GHz) EPR spectroscopy was able to identify the g-tensors of three [4Fe–4S] clusters  clusters have also been reported on other SPASM domain-containing rSAM enzymes that catalyze the S–C6 (S–Cα) , RumMc1 –Cα) ) rSAM enzymes must also be understood. EPR spectroscopy, among other techniques, has played a crucial role in mechanistic characterizations in rSAM enzymes. Here, we focused on discussing four examples SPASM/twitch domain-containing rSAM enzymes characterized by EPR spectroscopy.BtrN, PqqE and SuiB all perform two-electron oxidation reactions. The AuxI cluster in SuiB was observed to accept an electron from the radical intermediate Lys–Trp• . By exteUnderstanding the components of these enzymes is important for realizing their applications, such as new avenues for drug (bio)synthesis and protein engineering efforts. EPR spectroscopy is unparalleled in its ability to directly observe, identify and characterize fleeting paramagnetic intermediates, as well as the complicated iron–sulfur clusters in rSAM enzymes. Despite a great abundance of SPASM/twitch domain-containing rSAM enzymes, very few have been investigated by EPR spectroscopy. EPR studies of additional systems are needed to cement the role(s) of the SPASM/twitch domains in catalysis. Moreover, for SPASM domain-containing rSAM enzymes, the role of AuxII cluster remains unclear. Perhaps studying the enzymatic reactions under conditions closer to the in vivo ones, such as using biological reductants , may rev


Spatial resolution of about 30 nm was demonstrated over 5 μm maps, with rotation and strain resolutions of approximately 10−4. The magnitudes of surface strains and, especially, rotations peaked within and adjacent to isolated domains at values of approximately 10−2, i.e., the tetragonal distortion of BaTiO3. The conjugate stresses between a domains peaked at about 1 GPa, and principal stress analysis suggested that stable microcrack formation in the c domain was possible. The results clearly demonstrate the applicability of EBSD to advanced multilayer ceramic capacitor reliability and strongly support the coupling between the electrical performance and underlying mechanical state of BaTiO3-containing devices.Cross-correlation of electron backscatter diffraction (EBSD) patterns was used to generate rotation, strain, and stress maps of single-crystal tetragonal barium titanate (BaTiO As a consequence, to minimize elastostatic and electrostatic energy  × [010] × [001], electrically poled such that the majority of the sample was a single c domain, i.e., a domain with c axis perpendicular to the large faces. A single large face of the sample as received was prepared by chemical-mechanical polishing. An additional polishing step using colloidal silica for 5 min was performed on this face. Optical micrographs of two regions of the polished surface are shown in c axis nearly parallel to the surface and an a axis perpendicular to the surface and will be referred to as isolated a domains. Such surface features are not often reported, although isolated bulk a-c domain structures are common, and surface steps associated with bulk 90° domain boundaries  are apparently usual in crystal growth studies , ≈ ± 0.01, which is the relative tetragonal distortion of BaTiO3 and the rigid-domain rotation angle ; the scale and axis orientation are indicated. Perhaps the most striking feature of ω13 rotation component. There is a distinct negative rotation region localized on the large a domain on the left (blue). In addition, there are large positive rotations localized on the smaller a domains to the right and extreme left, and a weak positive rotation adjacent to the large domain . The ω12 and ω23 rotation components exhibit few distinct features. Conversely, the major feature in the strain field is the distinct positive ε22 region in the c domain between the a domains in the center of the image (red). In addition, there is a negative ε11 region localized on the a domain to the left and a negative ε33 region between the a domains (both blue). In these laboratory Cartesian coordinates, the ε12, ε23, and ε13 shear strain components exhibit few distinct features, and the strain field is dominated by the normal strains. More detail and consideration of the strain and associated rotation variation about the isolated a domain are given in the Appendix, noting the similarities with the lamellar domains observed previously  + c[001] and line direction perpendicular to the page (X2 direction). b = b1 + b2, where b1 = a[100], and b2 = c[001], with one set of extra half-planes of unit cells below the dislocation and normal to the X1 direction, and a second set to the right of the dislocation and normal to the X3 direction.Inspection of a domain from the c-domain matrix. The number of dislocations, N, is set by the size of the isolated domain and can be approximated by N ≈ θrl/c, where l is the domain width. For the left domain in l ≈ 0.7 μm, and for BaTiO3 . This surface inclusion domain structure, delimited by parallel rotation domain boundaries, should be compared with a similar structure delimited by intersecting domain boundaries studied earlier , and the number of dislocations was set by the thickness of the sample.r BaTiO3 , c ≈ 0.4 earlier . In the c-domain crystal indicated It is clear that subsurface termination of domains within differently oriented matrices requires accommodating dislocations to maintain structural compatibility. Recent observations  using daervation , 64. In ervation , 66. Sucω13 extending over approximately 1 μm on the left and 0.5 μm on the right, somewhat inconsistent with the abrupt, stepped variation implied by a domain is not formed by rigid rotation but by gradual rotation, and a domains with respect to c domains, contrary to observation. Similarly, the Ginzburg-Landau-Devonshire (GLD) model, which even takes into account finite domain wall thickness, predicts that stresses and strains are localized to the nanoscale region around the domain wall [Longer-range behavior is highlighted in ain wall . Howeverain wall , 69 may 3 X7R formulation [Finally, it should be emphasized that the results presented here do not address MLCC structures directly, but they do provide a measurement tool and demonstration measurements with the appropriate spatial and deformation resolutions to investigate reliability-limiting features that might arise in commercially fabricated MLCCs. Such MLCCs often use the doped BaTiOmulation , 2, with5−4 and conjugate stress resolutions of approximately 10 MPa. The capability was demonstrated here on domain features in tetragonal BaTiO3. In particular, EBSPs from isolated, sub-micrometer a domains, surrounded by 90° domain boundaries within a c-domain field, were indexed for orientation, and detailed 2-D maps of strain, rotation, and stress were generated. The maps indicated that the surface deformation of such isolated domains is dominated by out-of-plane rotation, although the in-plane normal strains are still significant. The strain profiles across isolated domains were very similar to those observed across quasi-periodic lamellar and bundled domains, suggesting a commonality in domain boundary structure and within-domain relaxation for different domain microstructures. Maps of principal stress values were generated, indicating tension in the c-domain region separating isolated a domains. Calculated stress trajectories and assessment of stress values suggested that isolated microcracks in such locations were possible in these BaTiO3 microstructures. The surface rotation profile across an isolated a domain within a continuous c-domain field constrained the subsurface surface termination of the a domain to include a dislocation with Burgers vector inclined to the surface. The results clearly demonstrate the applicability of EBSD measurements to commercial MLCC structures and reinforce the linkage between electrical performance of MLCCs, and other BaTiO3 devices, and the underlying mechanical features through the domain structure.Measurements of deformation and stress using high-resolution EBSD can be extended to spatial resolutions of 30 nm with strain and rotation resolutions of approximately 106a and c domains in barium titanate, supporting claims made in the text. Specifically, a domain as compared with those previously observed in lamellar and bundled domains and highlighting the resolved strain variations in 30 nm steps. Fig. A2 shows strain maps of an area within c domain.This Appendix provides strain information for isolated


Sorghum has a long history of use in the production of different types of bread. This review paper discusses different types of bread and factors that affect the physicochemical, technological, rheological, sensorial, and nutritional properties of different types of sorghum bread. The main types of bread are unleavened (roti and tortilla), flatbread with a pre-ferment (injera and kisra), gluten-free and sorghum bread with wheat. The quality of sorghum flour, dough, and bread can be improved by the addition of different ingredients and using novel and traditional methods. Furthermore, extrusion, high-pressure treatment, heat treatment, and ozonation, in combination with techniques such as fermentation, have been reported for increasing sorghum functionality. Sorghum bicolor L. Moench) is a grass belonging to the Andropogoneae tribe of the Poaceae family  and is among the top five cereals in the total world production after wheat, maize, rice, and barley [4 photosynthetic pathway. Sorghum is a drought-tolerant crop and has advantages over similar crops such as corn in areas of limited rainfall [Sorghum . In terms of traditional sorghum bread products, almost all relevant manuscripts’ findings were included in the present study. However, in terms of sorghum gluten-free bread and wheat bread, mostly studies conducted after the 2000s were included. Papers were selected on an inclusive basis as the literature was limited in terms of sorghum used in bread and bread-like products, especially related to the use of 100% sorghum.Roti, which is commonly consumed in Western and Central India, is an unleavened bread typically made with pearl millet or sorghum flour ,23,24. STo evaluate the quality of roti, two different aspects were used: (a) dough handling properties, or how easily the dough stretches to make thin pancakes, and (b) sensory attributes such as softness, chewing properties, dryness, and absence of bitterness .Pericarp color, endosperm type, and texture significantly affect the quality of roti. The most preferred grains in roti preparation are white/pale yellow, dense, and round grains . Murty eGrain structure , dough properties , and roti sensory characteristics  were all affected by the environment, season, year, and genotype and year interactions . Roti quIn addition to relationships between grain physical traits and roti quality, there were significant correlations between roti quality and the chemical properties of sorghum grain reported. Though it is not bread, Aboubacar and Hamaker  showed tNandini and Salimath  studied In terms of the flavor characteristics of roti, a positive correlation was found between flavor and protein, amylose, or ash content . CarbohyDue to the properties of sorghum flour and its impact on starch digestibility , there hThe impact of sorghum grain components on roti quality has been the subject of a wide range of studies, but the impact of processing methods on roti quality has received less attention. More research must be conducted on the use of various approaches to improve the quality of roti because there has only been a small amount of research on various processes and techniques.Tortillas with alkali-cooked corn are commonly consumed in Mexico and Central America. However, sorghum or sorghum and corn blends are often used to bake tortillas because sorghum has a higher grain yield in hot and dry climates and is often a less expensive ingredient in certain Latin American countries ,52. MoreNixtamalization is the traditional process used to produce corn flour used in tortilla making. In this process, corn is boiled in water with a low (1–5%) level of calcium hydroxide, soaked overnight, washed, and then ground in a stone grinder. The obtained flour is called “corn masa”. The masa can be wet or dried to obtain dry masa flour, which is also called an “instant” tortilla mix . Masa isNixtamalization also reduces the total phenolic content of sorghum grains. Luzardo-Ocampo et al.  comparedThe majority of research on sorghum nixtamalization has focused on antinutrients and phenolic content. However, nixtamalization also improves sorghum protein bioaccessibility in tannin-containing sorghum by depolymerizing condensed tannins and disrupting protein–tannin complexes . InteresDifferent levels of sorghum bran  have been added to corn tortillas before or after the extrusion process to improve the nutritional quality of extruded nixtamalized corn flour tortillas ,61. TotaIn another study, researchers found that sorghum bran addition (5 or 10%) prior to extrusion increased free phenolic acid content and in vitro antioxidant activity . TortillTortillas prepared with whole white sorghum had a softer texture and darker color than those made with white corn . BedollaThe kernel size, texture, and structure of sorghum grain affected the quality of tortillas as much as they impacted the quality of roti. Khan et al.  reportedSorghum hybrids and commercial sorghum flour were also evaluated to make gluten-free sorghum tortillas . TortillInjera is an important food staple in Ethiopia, Eretria, and portions of Somalia ,77. InjeThe production of injera from sorghum has been conducted by several research groups , with reEragrostis curvula (Shrad.) Nees, with low levels of sorghum (5 and 10%), and reported that the texture, taste, and appearance of the teff injera were improved with the addition of 5% sorghum.In addition to cultivar selection, other methods have been investigated to improve the quality of injera made with sorghum. Decortication and the use of sorghum-teff blends were also evaluated as techniques to enhance the quality of injera . DecortiThermal processing has an impact on the nutritional content of food products . AccordiKisra is a Sudanese bread made from sorghum, which is similar to injera but is smaller, thinner, and lacks a spongy texture . OverallAs with other sorghum-based foods, the sorghum cultivar used for kisra production has a significant effect on the final quality of the product. The evaluation of Sudanese sorghum cultivars during cooking and by sensory evaluation found that kisra quality varied among the sorghum samples . SorghumResearch has been conducted to combine sorghum flour with other flours to improve the nutritional quality of kisra. For example, kisra made with sorghum flour plus bean protein isolates had higher protein and lysine content compared to kisra made only with sorghum . The useCeliac disease, as the most prevalent genetic disorder in humans, is a food intolerance that lasts a lifetime. HLA DQ2 and DQ8 haplotypes are shown to contribute to the genetic factors of celiac disease. Although genes found in humans increase the likelihood of developing celiac disease, environmental factors have also been proven to have a role in the development of this autoimmune disease . IndividCereals , pseudo-cereals , legumes , seeds (flax seeds and pumpkin seeds), nuts , tuberous rhizomes , and other types of raw materials (plantain and coconut) are used in gluten-free diets. As one of the gluten-free grains, the potential use of sorghum flour was evaluated in gluten-free pan bread ,115. As In terms of the nutritional aspects, five different gluten-free breads  were evaluated by Wolter et al. . Among tThe particle size of grain flour is highly important since it determines the available surface area for different types of reactions during bread making. Milling increases the exposure of starch to hydration and enzymatic action, and this results in increases in water absorption and starch digestibility of flours during dough making . SchoberThe blend of gluten-free flour, starches, and hydrocolloids are the core ingredients of gluten-free sorghum breads. Corn, tapioca, gelatinized tapioca, and potato starches are the most commonly used starches with sorghum flour ,128,129.Researchers have also studied the effects of the levels of fermented cassava, sweet potato, and sorghum flour on rheological and textural properties . Breads Hydrocolloids, along with starch and flour, are often used in gluten-free flour blends to enhance the rheological qualities of dough in the absence of gluten ,137,138.To evaluate the sensory properties  of chemically leavened gluten-free sorghum bread with different starches and hydrocolloids, a lexicon with 28 attributes was developed by a panel highly trained in descriptive sensory analysis. The results showed bread with rice starch–xanthan gum or tapioca starch HPMC had a significantly better appearance, whereas bread with potato starch–xanthan gum and rice starch–xanthan gum had a significantly better texture/mouthfeel . Gluten-Emulsifiers assist in the incorporation of air, the blending and emulsification of ingredients, dough stability, water absorption, texture and volume, and the extension of the shelf life of baked products ,145. Fur−1) were examined in gluten-free batter and bread with sorghum. The levels of α-amylase did not have any impact on the rheology of the batter, but higher levels of enzyme in sorghum bread caused a decrease in crumb firmness, cohesiveness, springiness, resilience, and chewiness, but an increase in adhesiveness [Enzymes are widely used in baking and are highly effective in gluten-free systems ,155,156.siveness . In anotsiveness . Glucosesiveness . Proteinsiveness . The resHeat–moisture treatment, high-pressure treatment, extrusion cooking, etc., have also been used as innovative approaches to improve the quality of sorghum bread ,163,164.Saccharomyces cerevisiae, Pediococcus pentosaceus, and a mixture of both with control as breads with baker’s yeast. The control breads had a higher specific volume than sourdough bread. The height, texture, shape, crust color, and cracks did not change by sourdough application, but sorghum breads with baker’s yeast had lower scores in taste and overall acceptability [Sourdough has been used as a processing technique for centuries, and it has gained popularity recently . Sourdoutability . The addtability .Weissella cibaria MG1, Lactobacillus reuteri VIP, and L. reuteri Y2 were used for forming dextran, reuteran, and fructan, respectively, and also produced organic acids. EPSs were found to be more effective than organic acids in improving the quality of breads prepared with 10 or 20% sourdough. Breads and batters without sucrose and sourdough were used as controls in this research. Batters produced from sourdough had less strength and elasticity. Moreover, the degradation of sucrose to glucose and fructose increased the CO2 production of yeast during fermentation. Organic acids in the control of sourdough breads led to the hardening of the crumb. The impact of the organic acids was masked by the EPSs produced during sourdough fermentation, resulting in a softer crumb in both fresh and stored sorghum bread. Sourdough application did not significantly affect the specific volume of bread, except for breads with 20% sourdough, as demonstrated by L. reuteri Y. Overall, the results of this study showed that EPS formed during sourdough fermentation can be successfully applied to gluten-free sorghum flours to improve their bread-making potential. Schwab et al. [Lactobacillus reuteri LTH5448 or Weissella cibaria 10 M were used to ferment sorghum sourdough, producing fructooligosaccharides and levan, and isomaltooligosaccharides and dextran, respectively. The bread with W. cibaria 10 M was softer than bread prepared with L. reuteri LTH5448. Olojede et al. [Pediococcus pentosaceus SA8, Weissella confusa SD8, P. pentosaceus LD7 and Saccharomyces cerevisiae YC1 to evaluate the structure of batter and bread and the nutrient properties of bread. Doughs with Pediococcus pentosaceus LD7 had the highest storage and loss moduli, whereas dough with P. pentosaceus SA8 sourdough had the lowest viscoelastic structure. Breads with P. pentosaceus SA8 and S. cerevisiae YC1 had the highest total dietary fiber but the least protein content. P. pentosaceus LD7 caused the most significant effect on the rheological properties [Another study was conducted to determine whether exopolysaccharides (EPSs) produced from sucrose during the sourdough process could replace hydrocolloids in gluten-free breads . For thib et al.  also come et al.  producedoperties . The aggResearch has shown that the use of sourdough improves consumer acceptability, antioxidant properties, and the protein digestibility of gluten-free breads . The addDairy and egg products have long been used in bread making because their proteins are highly versatile and easily incorporated into the dough. Milk proteins, as an example of animal protein, helped to improve crust browning but interfered with the starch gel by competing for water and disrupting the gel’s uniformity, resulting in a lower bread height, a higher bake loss, a lower crumb cohesiveness, and a collapsed top . The addOzone is a powerful oxidizing gas that occurs naturally. It can be used to disinfect food in direct contact and has been used in different applications, such as washing and tempering wheat, controlling insects and fungus in stored grain, as well as improving flour quality . Ozone wWheat has been a staple cereal in bread for centuries since wheat, protein, and gluten, are highly functional in the bread-making process. While bread made with sorghum flour is high in certain nutrients, sorghum alone does not contain the functional proteins needed for bread making ,176,177.The majority of sorghum proteins are encapsulated within protein bodies, which renders the proteins unavailable for interaction during food processing and freeing the proteins from the protein bodies has been suggested as one method to improve the functionality of sorghum flour . SorghumThe addition of gluten proteins has also been tested for its impact on sorghum–wheat composite flour and bread. Exogenous gluten protein considerably improved wheat–sorghum flour composite dough strength . Water a2, a lower total area, a lower pore area fraction (%), and a lower number of small cells (<2 mm2) compared to the control loaves. Nevertheless, the average pore size of the bread with extruded sorghum flour was smaller than that of the control bread. The addition of xanthan gum improved both the non-extruded and extruded sorghum wheat dough by increasing the water absorption and elasticity, but it had a negative impact on the textural properties of the final breads. Breads had harder textures when extruded sorghum flour and xanthan gum were used [The extrusion cooking of sorghum has also been used in sorghum–wheat breads. Jafari et al.  investigere used .L. plantarum and L. brevis in wheat–sorghum composite bread was tested. In terms of textural properties, bread with different levels of dry nabag (Ziziphus lotus) pulp powder and fermented sorghum flour had statistically similar textural properties, except bread with 100% wheat [Sorghum grain was malted to decrease the gelatinization temperature and enhance the water-holding capacity of sorghum flour, hence overcoming the problems caused by the use of sorghum flour in composite breads . Four di0% wheat .To evaluate the effects of high pressure on composite flours, high-pressure-treated  sorghum flour was replaced with 40% of untreated wheat flour. Based on the results, high-pressure treatment provided better sensory scores and exhibited higher antiradical activities than those prepared by a conventional bread-making process and gluten incorporation. In addition, most physicochemical  and nutritional features  were not appreciably impaired by high-pressure treatment .In terms of the nutritional properties, the addition of 20, 30, and 40% sorghum flour to composite flour and bread decreased gluten, protein, sugar, phytic acid, and essential amino acids  but increased crude fat and ash . SimilarIn addition to functional and nutritional considerations, sensory analysis is an important part of consumer acceptance of any product, and therefore sorghum breads and sorghum composite breads. The rapid descriptive sensory descriptive techniques, check-all-that-apply (CATA) and optimized descriptive profile (ODP), were used by de Aguiar et al.  to distiIt is critical to assess the rate of success for genetic improvement on a regular basis in order to find sorghum genotypes that may be employed in future breeding research to improve nutrient content and quality. Further research into the usage of preprocessing technologies should be carried out in order to improve the quality of sorghum flour and, as a result, the total product quality. Future research should also concentrate on the effects of the environment and crop management on sorghum quality. It is necessary to optimize the bread formulas and conduct a cost analysis. The comprehensive characterization of quality criteria should be the focus of future studies to improve high-sorghum breads .Sorghum flour has been used to produce a wide range of bread and bread-like products, from “Western” style pan breads to “traditional” fermented flat breads and wrap-like products. As consumer preferences change, preferences for the style and type of bread products can also change. The sustainability and ability of sorghum to be grown in hot and dry climates, along with the unique health attributes found in sorghum flour, make sorghum an attractive flour for both gluten-free markets and functional food markets (including sorghum-only and wheat-sorghum composite products). Sorghum flour lacks functionality, and innovative processing techniques and technologies have been evaluated for improving the functional properties of sorghum flour and final product quality.Sorghum flour and/or different types of flours can be used to make pan breads (gluten-free and sorghum–wheat composite pan breads) and flat breads . The most preferred grains in roti preparation are white/pale yellow, dense, and round grains. The pericarp color of sorghum grain, endosperm type, and texture significantly affect the quality of roti. The use of corneous grain up to a certain content improved dough and roti quality. There have been reports of the strong connections between roti quality and the chemical characteristics of sorghum grain as well as between roti quality and grain physical characteristics.The quality of the tortillas was improved by using various percentages of sorghum flour. The quality of tortillas was influenced by the sorghum grain’s kernel size, texture, and structural composition. Both nixtamalization and cooking increased the bioaccessibility of the total phenolics and flavonoids.Several sorghum genotypes were found to be superior to teff in making injera. Thus, the quality of injera was found to be dependent on sorghum cultivar.As sorghum proteins lack the functionality of wheat gluten proteins and differs in other functional properties compared to wheat flour, substantial research has been conducted on methods to improve the functionality of sorghum for the production of pan breads. Sorghum grain germination has been proven to be advantageous for strengthening the sensory and nutritional qualities of cereals as well as the functional aspects of flour. The impacts of additives used to enhance the quality of sorghum bread on the nutritional value and quality of sorghum gluten-free bread have been well characterized. However, the substances used in gluten-free imitations largely determine their effects.Variations in grain hardness and the resulting variations in starch damage in sorghum flour may be significant sorghum quality characteristics for the manufacturing of gluten-free pan bread. Replacing the flour–starch base with whole grain flour produced acceptable gluten-free rolls.Sorghum flour has been proven to produce bread with quality similar to wheat flour when used in small amounts with wheat flour. Sorghum additions, however, at greater amounts, reduced the volume and porosity of the crumb, degrading the quality features of the bread. Although the physicochemical and rheological qualities were adversely affected, the sensory quality of the bread produced using the combination of wheat and white grain sorghum flour was acceptable.Traditional processing methods contain many benefits for impacting sorghum flour and food quality, and these techniques should not be lost with changing consumer preferences. Combinations of novel processing techniques such as extrusion, high-pressure treatment, heat treatment, and ozonation with techniques such as fermentation may provide new avenues for improving sorghum flour functionality.To investigate and develop processing techniques that improve sorghum flour functionality and end-product quality, emphasis needs to be placed on identifying sorghum germplasm with improved properties for the production of specific foods, along with breeding efforts to develop and improve sorghum for food functionality and quality.Sorghum is known for being a genetically diverse crop, and several studies have identified sorghum germplasm that is superior for making specific foods. Selecting sorghum for food functionality and quality and improving nutrition for specific foods can impact significant portions of the world that rely on sorghum as a basic food staple.