Saccharomyces cerevisiae, where its components were first discovered and extensively studied, the PPP plays only a minor role. In contrast, PPP and glycolysis contribute almost equally to glucose degradation in other yeasts. We here summarize the data available for the PPP enzymes focusing on S. cerevisiae and Kluyveromyces lactis, and describe the phenotypes of gene deletions and the benefits of their overproduction and modification. Reference to other yeasts and to the importance of the PPP in their biotechnological and medical applications is briefly being included. We propose future studies on the PPP in K. lactis to be of special interest for basic science and as a host for the expression of human disease genes.The pentose phosphate pathway (PPP) is a route that can work in parallel to glycolysis in glucose degradation in most living cells. It has a unidirectional oxidative part with glucose-6-phosphate dehydrogenase as a key enzyme generating NADPH, and a non-oxidative part involving the reversible transketolase and transaldolase reactions, which interchange PPP metabolites with glycolysis. While the oxidative branch is vital to cope with oxidative stress, the non-oxidative branch provides precursors for the synthesis of nucleic, fatty and aromatic amino acids. For glucose catabolism in the baker’s yeast  Saccharomyces cerevisiae holds a leading position not only in classical fermentations but also as a key model organism for eukaryotic cell biology [For a long time investigations of central carbohydrate metabolism in yeast has raised comparatively little scientific interest. This has changed in the last few years with their increasing relevance for novel biotechnological processes and the enormous potential of the new discipline of synthetic biology ,2. Moreo biology ,4, other biology ,6,7.S. cerevisiae, we will primarily concentrate on the milk yeast, Kluyveromyces lactis, for its close relationship and model character [Candida albicans, for its importance as an opportunistic human pathogen [In this context, we decided to give an overview of the role of the pentose phosphate pathway, further abbreviated as PPP, and its constituting enzymes in yeast sugar metabolism, as compared to glycolysis. Besides the best studied yeast haracter , but alspathogen ,10, and pathogen  and on ypathogen ,13. Furtpathogen ,17,18,19The PPP is generally depicted with two branches : (i) theHaloferax volcanii, a member of the haloarchaea [S. cerevisiae revealed that carbon can also be fed into the PPP independent of the oxidative branch. This is achieved via an activity of the glycolytic aldolase enzyme, Fba1, which condenses dihydroxyacetone phosphate with erythrose-4-phosphate to generate sedoheptulose-1,7-bisphosphate  are ancient biological processes which ensure energy production from sugar sources and provide the building blocks for nucleic and amino acid syntheses. Thus, they operate and fulfill essential roles in cells from bacteria, fungi, plants and animals, including humans, where defects in enzymes of the PPP are associated with serious diseases . In oarchaea . In addiIn the following section, we will discuss the enzymes involved in the PPP one by one, comparing their features. Key parameters of the yeast enzymes and their encoding genes are also listed in Glucose-6-phosphate dehydrogenase (G6PD), discovered in the first half of last century by Otto Warburg as “Zwischenferment” , has ceS. cerevisiae, the active enzyme appears to be a tetramer, whose dissociation into dimers and decrease in activity could be triggered by NADPH [ZWF1 gene, which has been cloned and deleted from the haploid yeast genome by various groups [ZWF1 gene expression appears to be fairly constitutive, i.e., it is not induced under oxidative stress [zwf1 mutants is their dependence on an organic sulfur source reflected by their methionine auxotrophy, hence the synonymous designation of ZWF1 as MET19 [zwf1 deletion in several yeast strains [In by NADPH . The subs groups ,29,30,49e stress . Anotheras MET19 ,52. Grow strains ,29,30, w strains . The chrKlZWF1 gene has been cloned and deleted in the Pasteur-positive (Crabtree-negative) yeast K. lactis. The Pasteur effect is commonly interpreted as the downregulation of fermentation in the presence of oxygen, since respiration produces much higher ATP yields per molecule of glucose [K. lactis, but not in S. cerevisiae, the yeast that Pasteur was actually working on [KlZWF1 gene expression appeared to be constitutive, as is observed in the S. cerevisiae homolog. The Klzwf1 mutant showed a reduced biomass production on different carbon sources, suggesting that the enzyme activity is required for both fermentative and respiratory metabolism. KlZwf1 was found to occur both as a tetramer and as a dimer. Careful biochemical analyses indicated that conformational transitions, caused by the replacement of NADP+ for NADPH at an allosteric site in the subunits, trigger the formation of dimers of the tetrameric active enzyme and lead to an inhibition of its activity [The  glucose . Ironicarking on . There, rking on . Despiteactivity .Candida albicans, functional peroxisomal signal sequences were detected in CaZwf1 and also in the 6-phosphogluconate dehydrogenase CaGnd1 [CaZWF1/Cazwf1 mutants showed a reduced growth under hypoxic conditions and the authors state that the homozygous deletion would be lethal [In e CaGnd1 . Thus, we lethal .ZWF1 genes have also been studied in Kluyveromyces marxianus [Schizosaccharomyces pombe [Candida utilis [arxianus , and thees pombe  and Canda utilis . Except S. cerevisiae genome contains four genes for putative 6-phosphoglucono lactonases, named SOL1-SOL4 for the ability of its founding member—SOL1—to partially suppress the phenotypes of a los1-1 mutation when overexpressed. Only Sol3 and Sol4 show 6-phosphogluconlactonase activity and their overproduction does not suppress the los1 mutant. Thus, Sol3 and Sol4 were proposed to function in the PPP, while Sol1 and Sol2 are involved in nuclear tRNA export [sol3 deletion has been found to be more sensitive to oxidative stress in a large-scale screen [G6PD produces 6-phosphoglucono lactone, which originally was believed to spontaneously convert to 6-phosphogluconate. However, the A export . Quadrupe screen ,60.K. lactis, only one gene representing a homolog of SOL3 and SOL4 exists in the genome sequence , which may encode the 6-phosphoglucono lactonase, but has not yet been investigated. In analogy to S. cerevisiae, we assume that one other homolog of SOL1 and SOL2, also found in the K. lactis genome, would encode a protein not related to carbohydrate metabolism.For  browser , http://S. cerevisiae, due to the whole genome duplication, two encoding genes were found—GND1 and GND2—with Gnd1 contributing approximately 80% of the enzyme activity [gnd2 deletions do not display a strong phenotype under standard growth conditions, gnd1 deletions grow more slowly on glucose media, and in some strain backgrounds, not at all [GND2.A second NADPH is produced in the oxidative PPP by the action of 6-phosphogluconate dehydrogenase 6PGD; . Concomiactivity . Accordit at all . Growth t at all . NeitherK. lactis, which has not undergone a whole genome duplication, and a Klgnd1 deletion is lethal in the background of the sequenced type strain, i.e., spores from heterozygous diploids carrying the deletion do not produce colonies after tetrad analysis on rich medium with yeast extract, peptone, and glucose as a carbon source .Only one homologous gene can be found in C. utilis [S. pombe. The latter works as a tetramer in contrast to the dimeric enzymes from other yeasts [6PGD enzymes have been purified from . utilis  and fromr yeasts .RPE1, have been constructed in a haploid strain of S. cerevisiae. While rendering the cells devoid of any detectable D-ribulose-5-phosphate 3-epimerase activity, they displayed a reduced growth under standard conditions as well as on minimal media with glucose as a sole carbon source [rpe1 deletions proved to be hypersensitive towards hydrogen peroxide [Null mutants in the sole gene for ribulosephosphate epimerase, n source . As expen source , since rperoxide . To our RKI1, is essential in S. cerevisiae, preventing the analysis of haploid null mutants [rpe1 reported above, are viable. A conditional mutant, rki1R189K, abolished more than 99% of the wild-type enzyme activity and rendered the cells auxotrophic for pyridoxine [K. lactis, a Klrki1 deletion, is also not viable . The gene appears to be essential in C. albicans as well, as only mutants with a heterozygous genotype, CaRKI1/Carki1, could be studied [The gene encoding ribosephosphate ketol isomerase,  mutants . The rearidoxine . Biochem studied .S. cerevisiae carries two genes encoding putative transketolase isozymes: TKL1 and TKL2. The lack of any detectable enzyme activity in vitro in crude extracts from a tkl1 deletion clearly indicates that this gene encodes the major isoform [tkl1 tkl2 double mutants proved to be auxotrophic for aromatic amino acids, whose synthesis requires erythrose-4-phosphate as a precursor  is a metabolite that serves to replenish the PPP with carbon. Under growth conditions when there is little need for the reducing power generated by the oxidative part of the pathway, S1,7P2 is produced and then dephosphorylated by a specific bisphosphatase, Shb17. The enzyme seems to be widely conserved amongst the different biological kingdoms. In fact, homologs of the SHB17 gene (renamed from YKR043c) of S. cerevisiae are present in the genomes of all other yeasts listed in the genome order browser , includS. cerevisiae relied on glucose molecules specifically labelled with 14C at different carbon atoms. They were based on determinations of the radioactive label in the carbon dioxide produced, which varies with the degradation pathway: while the CO2 liberated by the oxidative branch of the PPP carries the C1 carbon of the glucose molecule, purely glycolytic degradation and channeling into alcoholic fermentation through the pyruvate decarboxylase reaction generates CO2 only from C3 and C4 [S. cerevisiae under standard growth conditions [Early attempts to determine the relative contribution of the PPP to sugar consumption in 3 and C4 ,76. Fromnditions .K. lactis cells lacking either the KlPGI1 gene or the genes encoding the two subunits of the heterooctameric phosphofructokinase, KlPFK1 and KlPFK2, grew well on glucose media, already indicating that the flux through glycolysis is not absolutely essential in this yeast [S. cerevisiae cannot grow on glucose when it lacks Pgi1. This was attributed to glucose-6-phosphate being fed into the oxidative PPP, which would lead to the accumulation of NADPH that cannot be re-oxidized, because S. cerevisiae lacks transhydrogenase activities [K. lactis, so that an NADPH imbalance is not an issue [Kltal1 Klpfk1 Klpfk2 could not use glucose as a sole carbon source, as did the single Kltal1 or the double Klpfk1 Klpfk2 deletions. It was thereby concluded that the PPP and glycolysis both have sufficient capacities for glucose metabolization in K. lactis [Klpgi1 Kltal1 and Klpgi1 Klzwf1 double mutants likewise failed to grow on glucose as a sole carbon source [K. lactis, specific activities of key PPP enzymes, like KlTal1 and KlTkl1, were considerably higher than those of their counterparts in S. cerevisiae [By contrast, is yeast ,79. In ftivities . On the an issue ,82. Trip. lactis . Accordin source ,44. Consrevisiae ,44.C. albicans would suggest that, in this opportunistic pathogen, the pathway also contributes significantly to glucose consumption [Reduced growth rates under hypoxic conditions of strains being heterozygous for various mutations in genes of the PPP in sumption .S. cerevisiae cells growing on synthetic medium  are diverted into the oxidative part of the PPP. In rich medium containing yeast extract, peptone, and also glucose as a carbon source, less than 0.9% of the sugar is degraded by the PPP [0 state clearly requires the synthesis of nucleic acids for DNA replication and gene expression and triggers a transient increase in the carbon flux to be re-routed into the PPP [K. lactis has been estimated to be much higher, reaching up to 40% [It now has become possible to study metabolic fluxes directly by following the in vivo distribution of carbohydrates in growing yeast cells. These studies generally confirm that less than 2.5% of the glucose consumed by  the PPP . These p the PPP . In addi the PPP ,33,85. Ip to 40% .S. cerevisiae has been proposed to participate in the fastest response to oxidative stress, reacting within the range of seconds [TDH genes) and triosephosphate isomerase (Tpi1), which is accompanied by the activation of NADPH production through Zwf1 [S. cerevisiae and K. lactis [Regarding its regulation, the PPP in  seconds . This isugh Zwf1 . This haugh Zwf1 . This hyugh Zwf1 , is baseugh Zwf1 . In the ugh Zwf1 . Otherwiugh Zwf1 . Similar. lactis . Due to . lactis .ZWF1, GND1, GND2, and TAL1, but markedly not RPE1. Stb5 is also required for the proper induction of SOL3 and RKI1. As expected, its binding to the promoters of many of these target genes is activated by the addition of diamide as an oxidative stress agent [TKL1 also requires Stb5, as shown by its decreased transcript levels in a stb5 deletion mutant. Since gene expression of non-PPP is hyper-activated in such deletions, the authors concluded that Stb5 may act either as a transcriptional activator or repressor, depending on the target gene. Notably, its binding reduces the expression of the glycolytic PGI1 gene. The general function of Stb5 therefore lies in maintaining the NADPH balance [At the level of gene expression, the zinc-dependent transcription factor Stb5 appears to be the major activator of genes encoding PPP enzymes ,94,95. TS. cerevisiae has been employed for thousands of years as a workhorse for the production of beverages from hexose sugars by mankind [S. cerevisiae has been applied to the conversion of alternative carbon sources for second-generation biofuels, especially from pentoses [Scheffersomyces stipitis , which encode xylose reductase and xylitol dehydrogenase [Kluyveromyces marxianus [RPE1 was also shown to be beneficial [S. cerevisiae by employing the Gal2 transporter and expression of three bacterial genes for its conversion into xylulyose-5-phosphate  Hirogenase . Xylose arxianus . In simineficial ,107,108.neficial . In addiiewed in .Further details on the importance of pentoses and lignocellulosic sources for the production of next-generation biofuels, and the important role of the PPP for detoxification of oxidants like furfural produced in these processes, would go far beyond the scope of this overview, but have been extensively reviewed, e.g., in ,113,114.STB5, which encodes a positive transcription factor and enhances the expression of PPP genes, has been instrumentalized for this purpose [Besides bioethanol, alternative biofuels are being developed, which are based on the production of fatty acids, also serving as building blocks for oleochemicals for cosmetic purposes and as detergents and industrial lubricants ,116. As  purpose .S. cerevisiae are being developed, to increase the level of isoprenoids as precursors for the production of carotenoids, other nutraceuticals and food colorants in many industrial processes [ZWF1 has been combined with a reduced glycolytic phosphofructokinase activity to obtain a more reductive power [Moreover, platform strains of rocesses . In factrocesses . Again, ve power .Unlike the unwanted occurrence of xylitol as a by-product in bioethanol production from pentoses described above, xylitol is of value as a sweetener and a functional food additive, with proposed anticancerogenic effects. Heterologous expression of xylose reductase genes has been employed in this context for xylitol production in yeast .S. cerevisiae strain already manipulated to efficiently grow on xylose by expression of the xylose assimilating genes from S. stipitis was employed [Nostoc punctiforme were introduced into the platform strain, the native TAL1 gene was deleted, and TKL1 and STB5 were overexpressed.The immense capacity of synthetic biology in relation to the PPP was demonstrated by the production of shinorine in yeast. Shinorine is a secondary metabolite naturally produced by cyanobacteria that protects against the damaging effects of UV, which can be used in sun creams as an environmentally friendly additive ,122. Sinemployed . In thatManipulation of the PPP has also been employed to increase the supply of erythrose-4-phosphate for the generation of aromatic amino acids and the production of compounds derived from them, as exemplified in ,124,125.S. stipitis (P. stipitis), served as the first source for genes heterologously expressed in S. cerevisiae in bioethanol production [S. stipitis on xylose as a sole carbon source [S. cerevisiae [One of the yeasts extensively studied for its ability to metabolize xylose, oduction ,102. In n source . Yet, durevisiae . Pichia pastoris (Komagataella phaffii) has long been employed for heterologous protein production due to its high capacity and its efficient secretion system [ZWF1 and SOL3, were found to improve the production of human superoxide dismutase by almost a factor of four [S. cerevisiae, the approach of manipulating the PPP seems promising.The yeast n system . However of four . As simiK. lactis, K. marxianus has two important advantages for industrial applications: it can grow on xylose as a carbon source, although glucose and lactose are preferred, and it is more thermotolerant, i.e., it thrives at temperatures higher than 47 °C .These are just a few examples demonstrating that non-conventional yeasts and their PPP are of great interest for ongoing and future biotechnological applications. For a larger overview on these and other yeast species in applied pentose metabolism, the reader is referred to .The PPP has attracted considerable attention for its role in human health. A summary of diseases related to malfunctions of its components is given in Gene expression and/or activity of most of the PPP enzymes are upregulated in cancer cells, which involves different signaling pathways, with prominent components like PI3K/Akt, Ras, p53, and mTor (reviewed in ). The reWhile there are many regulatory functions exerted by the PPP, the majority of investigations concentrated on the reaction catalyzed by G6PD, since it is the first and rate-limiting step providing reductive power . MoreoveE. coli, it has also efficiently been produced in S. cerevisiae [S. cerevisiae appeared to give somewhat conflicting results, KlZwf1 from K. lactis displayed striking similarities to its human homolog [While the structure of human G6PD was studied predominantly from enzymes purified from revisiae . These i homolog . This ofThis is also true for the investigation of other PPP enzymes, which are much more rarely associated with hereditary diseases and have barely been studied in yeast systems. Thus, transketolase deficiencies were originally associated with their decreased affinity for binding the cofactor thiamine pyrophosphate (TPP). That this really causes the Wernicke-Korsakoff syndrome was questioned later . More reFinally, the biochemical properties of human transaldolase have been studied and compared to the enzymes from other sources . In humaTALDO gene, are reviewed in [S. cerevisiae or K. lactis. In this context, only an expression of human G6PD gene variants and the human RPIA gene in S. cerevisiae have been reported so far [S. cerevisiae [Other rare reports on diseases related to PPP, including progressive leukoencephalopathy caused by RPI deficiency and organ defects triggered by liver malfunction due to mutations in a iewed in . This std so far ,158. Howd so far , heterolrevisiae , as wererevisiae . AlthougSaccharomyces cerevisiae, but also throughout the biological kingdoms [The pentose phosphate pathway has attracted revived attention not only in the model yeast kingdoms . For yeaK. lactis as opposed to S. cerevisiae, it is surprising that very few studies have been dedicated to its genetics so far. As outlined above, only KlZwf1 and its mutants have been studied in some physiological detail [Kltal1 null mutants were obtained [S. cerevisiae, are more time-consuming and laborious in K. lactis [K. lactis will be addressed in the near future and the findings are expected to be largely applicable to its close relative K. marxianus. Moreover, with respect to the carbon flow into and within the PPP, modern metabolomic approaches are expected to yield more similar results to human physiology in K. lactis than in S. cerevisiae, as the latter is too specialized in alcoholic fermentation. The higher similarity to mammalian cell physiology also recommends K. lactis as a heterologous host to produce and study human isoforms and variants. In contrast to most other non-conventional yeasts, K. lactis shares the advantage of a similar life cycle with S. cerevisiae, thus participating in the “power of yeast genetics” [K. lactis will re-draw the attention of the scientific community as an alternative model organism to “the yeast” S. cerevisiae.With respect to basic research, and in the light of the importance of the PPP for carbohydrate metabolism in l detail ,32, whilobtained . This is. lactis , and ourenetics” , while aenetics” . We thus


Polyphenols are important bioactive compounds that are affected by processing. The consumer’s demand for minimally processed products contributes to the increase in non-thermal technologies such as high-pressure processing (HPP) in the food industry. This review is aimed at critically discussing the positive and negative effects of thermal treatment (TT) and HPP on the stability of different polyphenol families in agro-food products obtained from strawberry and apple, two of the most used fruits in food processing. Our findings show that the phenolic content was affected by processing, fruit type, polyphenol family, and storage conditions (time and temperature) of the final product. To increase shelf life, manufacturers aiming to preserve the natural content of polyphenols need to find the sweet spot between polyphenol stability and product shelf-life since the residual enzyme activity from HPP can affect polyphenols negatively. Strawberries and apples are fruits consumed worldwide, both fresh and processed , due to their desirable sensory characteristics, nutritional value, and bioactive compounds. The main bioactive compounds found are polyphenols, the most significant dietary antioxidants present in fruit and vegetables, with a wide variety of biological activities linked to the associated health benefits . These iIn particular, in strawberries, flesh and achenes have a different polyphenol profile. In the flesh, the major phenols are flavan-3-ols/proanthocyanidins (F3OLs/PACs) and anthocyanins (ATs), while in achenes, the highest concentrations are for ellagitannins (ETs) and ellagic acid (EA) ,6. SimilThere is growing consumer awareness of the importance of consuming food products that preserve nutritional and functional properties . ConsumeMeanwhile, non-thermal treatments include high-pressure processing, dehydration, freezing, pulsed electric fields, cold plasma, ultrasound processing, magnetic field, and ozone ,17. TherFurthermore, one of the most studied non-thermal treatments is HPP. It works with high hydrostatic pressure and is commonly used at the industrial level between 300 and 600 MPa for 3–5 min ,22. As aBriefly, given the above facts and considerations summarized as follows: (1) polyphenols are important bioactive compounds that are affected by processing, (2) consumers are increasingly demanding “minimally processed” products, and (3) several non-thermal processing technologies such as HPP are now prevalent on the market, here, the objective of this article is to conduct a review of the literature about the differences between TT and HPP on the impact in polyphenol degradation in strawberry and apple products, two of the most used fruits in food processing.We systematically searched, evaluated, and synthesized research articles on the effects of traditional TT and HPP and their subsequent storage on the main polyphenols found in strawberries and apples. In strawberries, we analyzed F3OLs/PACs, ATs, ETs, and EA. Whereas for apple, F3OLs/PACs, FOLs, DHCs, and HCAs were reviewed. The major databases for the topic were used . The search terms used were: polyphenols or proanthocyanidins or anthocyanins or ellagic acid or flavonols or dihydrochalcones or hydroxycinnamic acids and thermal treatment or high-pressure processing or high hydrostatic pressure and strawberry or apple.The search was focused on studies published over the last 10 years. Articles were included: (i) if the phenols were quantified by high-performance liquid chromatography (HPLC); (ii) when at least three studies were found for strawberry and apple identifying the effect of the related processing technology; (iii) when there was a control of fresh strawberry and apple or their unprocessed products. Articles were excluded: (i) when the analyzed sample was a mix of more than one fruit; (ii) when the HPP processing was combined with any thermal treatment higher than 50 °C; (iii) when the TT led to a concentration or reduction in the final product, e.g., jams.For comparison purposes, the quantification of the different strawberry and apple polyphenols in the literature were converted to mg/100 g FW (fresh weight) to provide values closer to the fruit servings used in nutritional studies. The conversion of values based on DW (dry weight) to FW assumed that a fruit retains 10% of the original fresh weight after drying.Overall, 26 articles were reviewed to address the study question: what are the effects of TT and HPP on the stability of polyphenols?Strawberry was the most studied fruit with 15 articles, whereas 11 were examined for apple products;A total of 19 articles reported the effects of thermal treatment and 12 for high-pressure processing. The reviewed studies examined 199 different trials at different processing and storage conditions .The concentrations reported in these studies for phenols of the same family were added. Each group’s total polyphenols were compared before and after processing, obtaining a percentage of increase or decrease attributed to the processing effect. A total of 4 of the 26 articles reviewed did not provide quantitative information to calculate these percentages, and therefore they were not included in the figures. The phenolic concentrations recorded after processing were considered control to determine the storage effect, and the results obtained during storage were compared against the control.This section will discuss the positive and negative effects of TT and HPP treatments and their subsequent storage on the stability of the main polyphenols in strawberries  and applProanthocyanidins, or condensed tannins, are plant secondary metabolites that could be found as oligomers or polymers of flavan-3-ol monomeric units. The most common monomeric building blocks are catechin, (epi)-catechin, (epi)-afzelechin, and (epi)-gallocatechin . F3OLs/PIn the case of strawberry, Nowicka et al.  recordedFor TT, a total of 8 studies with 30 trials including heat treatments from 70 to 98 °C during 0.4 to 15 min provided concentration data to calculate percentages of change of total F3OLs/PACs. Increments  from 4% to 1800% were observed on total F3OLs/PACs in apple puree and juice, pasteurized strawberry and strawberry pulp, and puree ,44,46,48Overall, HPP maintained the content of F3OLs/PACs closer to the fresh control in both fruits. In contrast, the impact of TT on the degree of change of F3OLs/PACs was positive or negative depending on the study, influenced by the matrix, the TT conditions, and the response of the fruit cultivar to the processing technology ,7 Figur. In addiFor TT, Stübler et al.  found a As mentioned before, in general, HPP showed minor variation in F3OLs/PACs levels compared to control. In the case of strawberry puree pressurized at 600 MPa for 1 min, Stübler et al.  detectedAnthocyanins (ATs) are water-soluble compounds found in different tissues of the plant, such as leaves, roots, flowers, and fruits . These pFor TT, 7 studies with 23 trials comprising temperatures from 70 to 100 °C for 1 to 15 min provided concentration data to calculate percentages of change of total ATs. Reductions  from 5% to 44% were observed in pasteurized strawberry, strawberry purees and pulp ,41,42,44Regarding HPP, a total of 6 studies, including 40 trials with pressurization conditions from 100 to 600 MPa for 1 to 20 min at 0–50 °C, were analyzed. Degradations  from 7% to 28% were reported in strawberry pulp and puree ,39,41,44In general, just after pressurization, the levels of ATs were preserved close to those found in fresh strawberries. In contrast, a more significant impact was observed in the degree of change of ATs due to TT, with a downward trend in both cases A.Since ATs are very chemically sensitive compounds, most of the studies registered the degradation of ATs after processing and storage. For instance, pasteurization of entire strawberries at 90 °C for 5 min resulted in a reduction of 5–35% of cyanidin-3-glucoside, pelargonidin-3-rutinoside and pelargonidin-3-glucoside ,32. HighInterestingly, many authors have reported different degradation percentages depending on the strawberry variety, concluding that the effect of TT and subsequent storage on ATs also depends on the response of the fruit variety to the treatment ,37,42. TAlthough overall TT led to degradation on ATs, some studies reported a positive impact after processing. Garzoli et al.  reportedThe effect of refrigerated storage (4–6 °C), from 14 to 180 days, on total ATs after different TT and HPP conditions is presented in Ellagitannins (ETs) constitute complex molecules with variable water solubility structured by one or more hexahydroxydiphenoyl (HHDP) moieties, which could be hydrolyzed to release ellagic acid (EA) . ETs andFor TT, 5 studies with 10 trials including temperatures from 55 to 90 °C for 1 to 15 min provided concentration data to calculate percentages of change of EA. Increases  from 8% to 66% were observed in pasteurized strawberries, strawberry pulp, and strawberry purees ,40,41,44In general, TT and HPP influenced the level of EA both positively and negatively depending on the conditions. Still, the most significant increases were observed as a result of heat treatment A.For TT, Cao et al.  reportedFor HPP, Cao et al.  reportedFlavonols (FOLs) are plant secondary metabolites that could be found in foods as aglycones or much more frequently as glycosidic conjugates . The mosFor TT, 3 studies with 17 trials including temperatures from 71 to 98 °C during 0.4 to 15 min provided concentration data to calculate percentages of change of total FOLs. Increments ranging from 4% to 69% were observed in five trials with apple juice and applesauce . In contOverall, HPP had positive effects on FOLs concentration. With TT, the results depended on the conditions and the apple varieties with a general trend to decrease their content .For instance, FOLs contents increased 49% and 69% after mild (71 °C/0.4 min) and intense (90 °C/14.8 min) pasteurization of apple juice, respectively, which indicates that thermal treatment favored the release of phenolic compounds and reduced PPO activity . AdditioAbout HPP, no significant differences were reported in quercetin levels after apple juice pressurization at 300 and 450 MPa for 5 min and in multi-pulsed HPP at 300 MPa x 3 pulses, each 5 min. However, after HPP treatment at 600 MPa for 5 min, a minor but significant increase from 0.73 to 0.91 mg/L (25%) was quantified for quercetin . These rThe dihydrochalcones (DHCs), phloretin and phloridzin, are characteristic compounds of apple and apple products. Since these compounds are exclusive of apples, these have been used to detect adulterations . DHCs leFor TT, 3 studies with 16 trials comprising thermal treatments from 71 to 98 °C during 0.4 to 15 min provided concentration data to calculate percentages of change of total DHCs. Increments 12 trials) ranged from 8% to 767% in applesauce and apple juice . Convers trials rOverall, TT and HPP changed the content of DHCs of apple products  positiveFor TT, Le Bourvellec et al.  reportedFor HPP, Szczepańska et al.  reportedp-coumaric, caffeic, ferulic, and sinapic acids [Hydroxycinnamic acids (HCAs) are the major subgroup of phenolic acids and may occur either in their free or conjugated forms, including amides, esters, and glycosides . The maiic acids . More fric acids . In applic acids . Ranges ic acids ,12. Wheric acids ,10. Someic acids ,90,91.For TT, four studies with 19 trials comprising heat treatments from 71 to 98 °C for 0.4 to 30 min provided concentrations data to calculate percentages of change of total HCAs. Increments  ranged from 8% to 925% in apple sauce and apple juice . On the In general, both TT and HPP caused degradation of HCAs after processing. Nevertheless, although a higher degree of degradation was observed after heat treatment, it also caused the most significant increase in two trials with apple juice  .p-coumaroylquinic acid. A total of 205% and 925% increments on total HCAs were reported after the mild (71 °C/0.4 min) and intense (90 °C/15 min) pasteurization of apple juice, respectively. The increase in HCAs could result from the favoring effect of thermal treatment in enzyme inactivation and the release of chlorogenic acid from the cell walls to the food matrix [p-coumaroylquinic acid after TT were due to apple variety. After cooking (95 °C/2 min) and pasteurization (90 °C/5 min), nine varieties experienced reductions from 1% to 48% in 5’-caffeoylquinic acid, whereas increases of 8%, 4%, and 30% were observed in Golden Delicious, Freiberg, and Granny Smith varieties, respectively.For TT, Alongi et al.  identifid matrix . These rd matrix , who cond matrix  reportedd matrix , suggestd matrix ,50. In aFor HPP, Marszalek et al.  found noThis review analyzed the effects of TT and HPP treatments on the phenolic compounds in strawberry  and apple  products. Our findings show that the effect on polyphenols content (positive or negative) was contingent upon the type of processing, type of fruit, polyphenol family, and the shelf-life conditions (time and temperature during storage) of the final product. The impact of TT relied mainly on the food matrix and the thermal stability of the different phenolic compounds.TT had positive effects in strawberry products, as was observed for F3OLs/PACs and EA. However, it had negative effects on the ATs content. These were due to the thermal instability of ATs and the enhanced extraction of EA and condensed tannins from achenes with thermal treatments. It is well known that ATs are heat-labile compounds, susceptible to oxidation and condensation reactions, which was confirmed in most of the studies where degradation of ATs was observed after TT. On the contrary, TT increased EA content due to the hydrolysis from ETs and release from the lignified matrix of the achenes.In apple products, TT had positive effects, significantly promoting the release of FOLs and DHCs from peel and seeds. However, most of the studies observed a negative effect of F·OL/PACs, principally due to the extraction processes that quantified flavan-3-ols oligomers rather than monomers. Nevertheless, the final concentrations were variable depending on the variety, and the TT conditions applied. HPP treatments maintained the concentrations of phenolic compounds closer to those of the fresh or unprocessed samples regardless of the food matrix.The impact of storage after TT and HPP had only been described for ATs in strawberry products. In general, TT has positive effects preserving better the ATs during storage. However, in the only study that examined the effect of HPP on ATs during storage, a negative effect was described showing a higher degradation than TT. Negative effects were also observed as the fast and pronounced degradation of FOLs, DHCs, and HCAs in apple products after HPP and storage.The phenolic compounds’ degradation after storage of HPP products could be due to the limitations in oxidative enzyme inactivation when thermal treatments were insufficient. From the industrial perspective, manufacturers aiming to preserve the natural content of polyphenols need to find the sweet spot between polyphenol stability and product shelf life. Further studies are recommended to compare how both technologies influence the content of the different families of polyphenols and their bioavailability and bioactivity.


After adjustment, these rates were stable between periods 1 and 2  and between periods 2 and 3 . Although more VLBW neonates were born during lockdown , this difference did not persist after adjustment . The LBW rates were similar during the three periods at 12.5% overall. The stillbirth rate was unaffected by the lockdown. Conclusion: The pregnancy outcomes  were not modified by the COVID-19 lockdown in our cohort study in France. Considering the discrepancies in results and methodological issues in previous published studies, there is not sufficient evidence to conclude that such lockdowns have any impact on perinatal outcomes.Objective: The effect of lockdowns during the coronavirus (COVID-19) pandemic on pregnancy outcomes remains uncertain. We aimed to evaluate the association between the COVID-19-related lockdown and pregnancy outcomes in maternity hospitals in France. Study design: This was a retrospective cohort study from six tertiary referral hospitals in different regions of France. Three 55-day periods were compared: pre-lockdown from 22 January 2020, lockdown from 17 March 2020, and post-lockdown from 11 May 2020 to 4 July 2020. We included all women who delivered singleton or multiple pregnancies, who delivered at ≥24 weeks of gestation and with birthweights ≥500 g. We documented gestational ages at the delivery of liveborn and stillborn infants (‘stillbirths’). These were categorized as having a very low birthweight , or a low birthweight . Adjustments were made for place of birth, maternal age, parity and diabetes, and hypertensive disorders, as well as for multiple pregnancies. Results: In total, 11,929 women delivered in the six selected centers. This figure is constituted of 4093, 3829, and 4007 deliveries in the pre-lockdown (1), peri-lockdown (2), and post-lockdown (3) periods, respectively. There were no differences in pregnancy outcomes between these three periods. Overall, birth rates <27 Lockdowns have been used by several health authorities to mitigate the effects of the COVID-19 pandemic on public health, which was caused by strains of the SARS-CoV-2 virus ,4,5,6. AThus, the potential effects of lockdowns on perinatal outcomes (and the magnitude of these effects), remain debatable. The objective of our study was to evaluate the adverse impacts of France’s lockdown on perinatal outcomes in a large population of pregnant women who were treated at six tertiary centers in different regions of France.A nationwide lockdown was implemented in France on 17 March 2020, in response to the COVID-19 pandemic, and continued until 10 May 2020. The population was asked to stay at home or to limit mobility drastically, to follow strict hygiene measures with handwashing, and to practice social distancing. During the lockdown, offices, shops, colleges, schools, and all institutions considered as nonessential were closed. However, after the government announced the end of the lockdown, some nonessential services remained closed, and the population was still asked to restrict social connections and to limit their mobility. This was still the case until the end of our study. These measures were similar in every district of France.This was a retrospective cohort study comparing three equal periods: (1) pre-lockdown from 22 January to 16 March 2020, (2) lockdown from 16 March to 10 May 2020, and (3) post-lockdown from 11 May to 4 July 2020. All singleton or multiple pregnancies delivering at ≥24 weeks of gestation with a birthweight ≥500 g  during the study period in six tertiary referral centers across France were included. Cases of termination of pregnancy were excluded. The six centers were located in: Lille in the north, Nantes in the west, Toulouse in the southwest, Strasbourg in the east, Poissy in Greater Paris, and Necker in central Paris. The six centers accounted for 3.8% of all births in France in 2020 . During the lockdown, COVID-19 spread heterogeneously, and therefore, the pressures on local healthcare systems varied. Indeed, the east of France and the region of Paris faced a critical situation, with intensive care units overwhelmed with COVID-19 patients, whereas the north, west, and southwest were initially spared this pressure [The following data were collected prospectively and analyzed retrospectively though computerized medical records: maternal age, parity (nulliparous versus multiparous women), singleton or multiple pregnancies, pre-pregnancy body mass index (BMI), diabetes with insulin required , and hypertensive disorders.+0–27+6), very premature (28+0–31+6), moderate-to-late premature (32+0–36+6), term (37+0–41+6), and post-term (>42+0). Determination of the gestation period for all women included in the study was based on the results of the first trimester ultrasound scan, routinely performed in France, or from the date of oocyte retrieval in pregnancies generated using assisted reproductive technology (ART). Birthweight was categorized as very low , or low . Elective delivery was defined as delivery after the induction of labor or during pre-labor Cesarean deliveries. Stillbirths at ≥24 weeks of pregnancy were also included in this study.Births were categorized according to gestational age in weeks and days (in superscript): extremely premature (23t tests or Mann–Whitney nonparametric U tests. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated by a logistic regression of places of births, maternal age, parity, multiple pregnancies, diabetes, and hypertensive disorders. Moreover, as a delay in the management of pregnancies complicated with VLBW or LBW was possible, Kaplan–Meier survival curves were calculated for gestational ages at delivery within each period. All analyses were performed with RStudio version 1.0.136  assuming a significance level of α = 0.05.Results were compared between different periods: Period 1 = pre-lockdown (from 22 January to 16 March 2020); Period 2 = lockdown (from 16 March to 10 May 2020); and Period 3 = post-lockdown (from 11 May to 4 July 2020). Categorical variables were presented as absolute numbers and percentages, and comparisons made using chi-squared or Fisher’s exact tests. Continuous variables were presented as medians with first and third interquartile ranges. Comparisons of continuous variables were made using Student’s n = 16, 16 and 19 during periods 1–3, respectively, with no significant differences; p > 0.05). Finally, 11,929 women were included during the study period, with 4093, 3829, and 4007 women in periods 1–3, respectively. There were 2, 33, and 2 hospitalized patients with a record of laboratory-confirmed SARS-CoV-2 virus infection in the six centers during periods 1, 2, and 3, respectively.During the study period, 12,154 women delivered after 24 weeks of pregnancy in the six centers. Of these women, 174 were excluded, as the pregnancies were terminated for medical indications (1.4%). Fifty-one home births which led to admission in one of the six maternity hospitals were also excluded  or between periods 2 and 3 , with this rate remaining stable during period 3 (60.0%).Pregnancy outcomes are summarized in p = 0.07). Although more VLBW neonates were born during the lockdown compared with before , this difference did not persist after adjustment, as described above . The LBW rates were similar during the three periods at 12.5% overall. The birthweight distributions were similar over the three periods  comparing 2 months after and 2 months before 9 March) [Since the beginning of the COVID-19 pandemic, several reports have showed decreases in the rates of preterm births, which appeared to be associated with the lockdown ,3,4,5,6.9 March)  and Khal9 March) . In our p = 0.01), while Stowe et al. did not report any difference at the national or inter-regional level in the UK [Other studies with fewer numbers of cases suggested that lockdown was not associated with reduced rates of preterm birth or with low birthweight ,8. Studin the UK .Several methodological issues might help to explain these discrepancies. Indeed, evaluating changes in gestational age over time and comparing preterm birth rates is challenging. In particular, according to the period selected and the length of time involved in these previous studies, differences in maternal demographics, clinical characteristics and other unmeasured confounders might lead to conflicting results . TherefoWe chose to select these six tertiary centers because each of them is the only referral center within their own network of maternity hospitals. This method made it easier to observe any changes in the incidence of preterm births, low birthweights, or stillbirths because these six centers receive referred high-risk women for imminent preterm births and women with fetal growth restrictions, especially before 32 and 34 weeks of gestation. This methodology makes us confident in our results, especially because the results were similar in each of the six tertiary centers. Finally, as highlighted by Goldenberg and McClure, investigators who do not see a reduction in preterm birth are less likely to publish their results . The main strength of this study was its data gathering was broadly geographically distributed across the country. This accounted for the heterogeneity of COVID-19 prevalence in the population. Data were collected prospectively in each maternity hospital, so that missing data accounted for less than 5% of all maternal and perinatal outcomes and provided a significant overview of the impact of the lockdown on pregnancies in France. Furthermore, for all women included in the study, gestational age at delivery was reliable because its determination was based on the results of the first trimester ultrasound scan routinely performed in France, or from oocyte retrieval in ART-generated pregnancies. We were able to report the proportion of spontaneous preterm births  and of medically indicated preterm births, as well as to classify preterm births rates by gestational age. However, our study had some limitations. We were not able to provide information on the prevalence of women affected by COVID-19 in our population . Indeed,Our study findings do not support the idea that lockdown during the COVID-19 pandemic might decrease the rates of preterm births and low birthweights or increase the rate of stillbirths.


P < 0.05); among 62 patients with malignant breast lumps of the 120 patients with breast lumps, 37 were patients with invasive ductal carcinoma, 8 with lobular carcinoma in situ, 16 with intraductal carcinoma, and 4 with mucinous carcinoma; among the remaining 58 patients with benign breast lumps, 28 were patients with fibrocystic breast disease, 17 with intraductal papilloma, 4 with breast hyperplasia, and 9 with adenopathy; the differences in shape, growth direction, edge, and internal echo of multimodal ultrasound imaging of patients with benign and malignant breast lumps had statistical significance (P < 0.05); the malignant constituent ratios of patients with breast density grades I to IV were 0%, 7.10%, 80.40%, and 100%, respectively. In short, the multimodal imaging diagnosis under the algorithm in this article was superior to CNN algorithm in all aspects; according to the judgment on benign and malignant breast lumps and breast density with multimodal imaging features, the higher the breast density, the higher the probability of breast cancer.This study aimed to analyze the diagnostic value of multimodal images based on artificial intelligence target detection algorithms for early breast cancer, so as to provide help for clinical imaging examinations of breast cancer. This article combined residual block with inception block, constructed a new target detection algorithm to detect breast lumps, used deep convolutional neural network and ultrasound imaging in diagnosing benign and malignant breast lumps, took breast density grading with mammography, compared the convolutional neural network (CNN) algorithm with the proposed algorithm, and then applied the proposed algorithm to the diagnosis of 120 female patients with breast lumps. According to the results, accuracy rates of breast lump detection (94.76%), benign and malignant breast lumps diagnosis (98.22%), and breast grading (93.65%) with the algorithm applied in this study were significantly higher than those  with CNN algorithm, and the difference was statistically significant ( Breast cancer is a malignant tumor with the highest incidence among women . AccordiWith the development of artificial intelligence and information technology, neural network has been applied in medical images . ElastogIn this study, 120 female patients with breast lumps who were admitted to our hospital from July 4, 2017, to July 5, 2020, were selected as the research samples, and all of them underwent multimodal imaging examinations. Then, based on the residual block and Google's Inception module, an artificial intelligence target detection algorithm was proposed and applied to analyze the multimodal images of patients. In addition, the imaging characteristics of patients' benign and malignant lesions were analyzed to comprehensively evaluate the value of multimodal imaging based on artificial intelligence target detection algorithms for early diagnosis of breast cancer.120 female patients aged 20–76 years with breast lumps in hospital from July 4, 2017, to July 5, 2020, were selected as research subjects. This study had been approved by the Ethics Committee of the hospital, and the patients and their families had understood this study and signed the informed consent form.The inclusion criteria were defined as follows: patients with breast lumps less than 20 mm in diameter; patients not receiving chemotherapy, surgery, or medication before surgery; patients accepted multimodal imaging examinations before surgery; patients with case results after biopsy.The exclusion criteria were determined as follows: patients not signing the informed consent; patients with incomplete clinical data; patients withdrawn from experiment midway due to personal reasons; patients in pregnancy and lactation.Multimodal ultrasound examination used color Doppler ultrasound diagnostic equipment, which was equipped with elastic imaging software Toshiba Aplio500/400, and the probe frequency was 6–13 MHz. Before the examination, patient was kept in a supine position under the guidance of medical staff, with arms raised to ensure the exposure of breasts and axillas, and then gray-scale ultrasound was used to give cross-sectional scan. During the period, it needs to observe distribution, size, and growth environment of the lesions, as well as their connection with surroundings, etc. Finally, by switching to the elastography mode, two-dimensional ultrasound image and the corresponding ultrasound elastography image could be observed via the real-time display function, and adjustment should be given according to the specific situation to obtain elastic ultrasound image.Mammography adopted MammoNovation Siemens FFDM with amorphous selenium solid-state detector, pixel size 60 mm (micrometers), 14-bit contrast resolution, and 3328 × 4084 pixels in matrix, to save the image acquired.The target detection algorithm was mainly divided into two-stage target detector and single-stage target detector: the former had high accuracy rate and took a long time for the interest area extraction specially, and the latter had low accuracy rate and a fast-running speed. According to the lumps and the characteristics of real-time ultrasound imaging, single-stage target detector was used to improve accuracy of breast lump detection by improving the network and optimizing the loss function. SSD model was constructed in this article by combining residual block with Google's inception block. Deep CNN was affected by many factors, and small blocks were reused in this article. Residual blocks of different network scales are shown in k frames in a certain position, targeting category c, and confirming each frame with 4 offset values, the number of convolution kernels K needed is as below:SSD is single-stage detector algorithm. It firstly draws forward features and reverse optimization from CNN, extracts interest areas, and then performs nonmaximum suppression to obtain the final prediction results. By setting m × n is as below:The number of results in the extracted feature map yijq=1 is used to indicate that a in series i matches with b phase in series j in category q, and yijq=0 does not match. According to the matching strategy in this article, it must be yijq ≥ 1. Total objective loss function can be expressed as below:The frame label of original image corresponds to the object border in the feature map, and the default box is matched with any groundtruth box (a). In this article, jaccard overlap (b) between the two was selected to be greater than the threshold 0.5, and intersection ratio of the two can be expressed as below:n refers to the number of matches between the two, loc refers to the input localization loss; conf refers to confidence loss, which is loss function of Softmax. Improvement was given to Softmax in this article. Binary grading is taken as an example, and cross entropy H is expressed as below:In , n referThe equation below can be obtained by combining  and 6)::6):(7)HPβT, the definition is as below:After improving cross entropy and adding coefficient By taking  in 7), , 7), it n characteristics patterns, the size SK of each characteristics pattern can be expressed asThe deeper the number of layers of many CNNs, the smaller the resolution of characteristics patterns. When giving prediction with Smax=0.93 and that of the lowest level Smin=0.30 are taken. When expressing with βr, it is as below:In , scale oThe width and height of each default frame can be calculated with When the ratio of width to height of the default frame is 1, one default frame is added, and there are total 6 frames in each feature map. Algorithm flow is shown in After obtaining interest areas, it needs to subtract B-mode ultrasound images from the elastic ultrasound images to obtain pure elastic information, which is then converted into H channel images. The conversion process is as below:r, g, and b are in 0–360. In this article, data was augmented by data enhancement to prevent overfitting, including image selection, translation, and flipping. The automatic feature extraction was realized before image training. The convolution operation is expressed as below:In , ranges l and l+1 refer to previous and current layers; b and W refer to bias and weight; E is output; and δ is activation function. After convolution, the maximum pooling and depooling shall occur:In , l and lThe network of lumps grading is in the following layers, and the nonlinear activation function Softmax is expressed as below:The subsequent process of CNN is deconvolution, which is used to update weights and biases, and seeks the optimum parameters by optimizing the multiclass cross entropy loss function.τ refers to all weights and biases and X refers to input. Algorithm flow is shown in In , τ referThe thinking of breast density grading under CNN is consistent with that of benign and malignant breast lumps diagnosis. This article just added residual block in the deep CNN to extract deeper features for the convenience of breast density grading. Algorithm flow is shown in   I. Breast lump detection with the ultrasonic image of target detection algorithm: workstation was dell-7910, two E5-2640v4 Intel Haswells CPUs were configured, the optimization algorithm was Adam, the maximum number of iterations was 10,000, the initial learning rate was 0.0001, weight was initialized randomly, and bias was initialized to 0.  II. Diagnosis of benign and malignant breast lumps with elastic ultrasound images under CNN: experimental framework was Keras, Tensorboard was used to monitor network training, workstation was dell-7910, two E5-2640v4 Intel Haswells CPUs were configured, the optimization algorithm was Adam, Batch size was 8, the maximum number of iterations was 6,000, and the initial learning rate was 0.0001.  III. Breast density grading by mammography under CNN: experimental framework was Keras, Tensorboard was used to monitor network training, workstation was dell-7910, two E5-2640v4 Intel Haswells CPUs were configured, the optimization algorithm was Adam, Batch size was 8, the maximum number of iterations was 3,000, the initial learning rate was 0.0001, weight was initialized randomly, and bias was initialized to 0.A and actual label B. When IoU > 0.75, lump detection was considered to be correct, and the accuracy rate should be calculated:Accuracy rates of the two algorithms in breast lump detection were compared, and intersection and union ratio (IoU) was used to evaluate the overlap between target area The two algorithms were compared in the sensitivity, specificity, and accuracy rate of benign and malignant breast lumps diagnosis:TP refers to correct identification of malignant lumps; TN refers to correct identification of benign lumps; FP refers to incorrect identification of malignant lumps; FN refers to incorrect identification of benign masses.In , 21), a, a21), aAccuracy rates of the two algorithms in breast density grading were compared. Breast density can be divided into four grades. Grade I is fat type with very low density (0%–25%); Grade II is scattered glandular type with low density (26%–50%); Grade III is uneven dense type with relatively high and uneven density (51%–75%); Grade IV is dense type with extremely high density (76%–100%).Pathological results and multimodal ultrasound imaging features  of benign and malignant lesions of the patients were recorded, and malignant constituent ratio of breast density grading of the patients was calculated:x ± s), the counting data was expressed in percentage (%), and the difference was statistically significant at P < 0.05.The data processing of this study adopted SPSS 22.0 version statistical software, the measurement data was expressed as mean value ± standard deviation .( < 0.05).P < 0.05). P < 0.05).P < 0.05).P < 0.05). The sensitivity (97.13%), specificity (94.32%), and accuracy rate (98.22%) of benign and malignant breast lump detection under the algorithm proposed in this study were significantly higher than those under CNN algorithm , and the differences had statistical significance (P < 0.05). The accuracy rate of breast density grading under the algorithm proposed in this study (93.65%) was significantly higher than that under CNN algorithm (79.54%), and the differences were significant statistically (P < 0.05). This indicated that the multimodal imaging of target detection algorithm under artificial intelligence proposed in this article could improve the accuracy rates of breast lump detection, benign and malignant breast lumps diagnosis, and breast grading. Such results were similar to the study results of Yoo et al. [At present, breast cancer has become a major disabling and fatal disease among middle-aged and elderly women worldwide, greatly affecting the physical and mental health of women. Vigorously publicizing the early detection, early diagnosis, and early prevention of breast cancer can effectively improve the 5-year survival rate of patients and effectively reduce the economic burden on the family and society of patients with breast disease –17. Multo et al. . The comP < 0.05). This was consistent with the study results of Ulaner (2019) [Later, it was applied to the diagnosis of 120 female patients with breast lumps, and the results showed that there were 62 patients with malignant breast lumps, including 37 patients with invasive ductal carcinoma, 8 with lobular carcinoma in situ, 16 with intraductal carcinoma, and 4 with mucinous carcinoma, and that there were 58 patients with benign breast lumps, including 28 patients with fibrocystic breast disease, 17 with intraductal papilloma, 4 with breast hyperplasia, and 9 with adenopathy. 65.5% (38/58) of benign lumps had regular shape, and 34.5% (20/58) had irregular shape, 70.7% (41/58) showed parallel growth direction, and 29.3% (17/58) showed nonparallel growth direction, 56.9% (33/58) had complete edges, and 43.1% (25/58) had incomplete edges, 20.7% (12/58) gave even internal echo, and 79.3% (46/58) gave uneven internal echo; 22.6% (14/58) of malignant lumps had regular shape, and 77.4% (48/58) had irregular shape, 95.2% (59/58) showed parallel growth direction, and 4.8% (3/58) showed non-parallel, 25.8% (16/58) had complete edges, and 74.2% (46/58) had incomplete edges, 71.0% (44/58) gave even internal echo, and 29.0% (18/58) gave uneven internal echo. The differences in shape, growth direction, edge, and internal echo of multimodal ultrasound images of patients with benign and malignant breast lumps were significant statistically (r (2019)  and indiInspired by multimodal imaging omics, this article combined residual block with inception block, constructed a new target detection algorithm to detect breast lumps, used deep CNN and ultrasound imaging in diagnosing benign and malignant breast lumps, took breast density grading with mammography, and gave comparison with CNN algorithm. Later, it was applied to the diagnosis of 120 female patients with breast lumps. The results indicated that multimodal imaging of target detection algorithm under artificial intelligence could improve the accuracy rates of breast lump detection, benign and malignant breast lumps diagnosis, and breast grading; the higher the breast density, the higher the incidence of breast cancer, according to the judgment on benign and malignant breast lumps and the density with multimodal imaging features. However, the sample size of patients selected in this study was small with simple source, and the results may be biased. Follow-up studies should further expand the inclusion of patient samples and conduct multicenter and large-scale discussions. All in all, the results of this article provided theoretical support for the early diagnosis and treatment of breast cancer.


P = 0.001). Also, increasing trends were observed in municipalities with high (N = 859) and very high SVI (N = 587). We identified two significant spatiotemporal clusters of deaths by COVID-19 in this Brazilian region (P = 0.001), and most high-risk municipalities were on the coastal strip of the region. Taken together, our analyses demonstrate that the pandemic has been responsible for several deaths in Northeast Brazil, with clusters at high risk of mortality mainly in municipalities on the coastline and those with high SVI.Currently, the world is facing a severe pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although the WHO has recommended preventive measures to limit its spread, Brazil has neglected most of these recommendations, and consequently, our country has the second largest number of deaths from COVID-19 worldwide. In addition, recent studies have shown the relationship between socioeconomic inequalities and the risk of severe COVID-19 infection. Herein, we aimed to assess the spatiotemporal distribution of mortality and lethality rates of COVID-19 in a region of high social vulnerability in Brazil (Northeast region) during the first year of the pandemic. A segmented log-linear regression model was applied to assess temporal trends of mortality and case fatality rate (CFR) and according to the social vulnerability index (SVI). The Local Empirical Bayesian Estimator and Global Moran Index were used for spatial analysis. We conducted a retrospective space–time scan to map clusters at high risk of death from COVID-19. A total of 66,358 COVID-19–related deaths were reported during this period. The mortality rate was 116.2/100,000 inhabitants, and the CFR was 2.3%. Nevertheless, CFR was > 7.5% in 27 municipalities (1.5%). We observed an increasing trend of deaths in this region (AMCP = 18.2;  In the past year, the world has been facing a new viral infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first cases emerged in the city of Wuhan , and since then, the virus has spread quickly on a large scale in several countries. The disease, termed COVID-19, was declared a pandemic by the WHO in March 2020 and has been causing significant social, economic, political, and public health impacts worldwide.Despite all the efforts and strategies instituted in several countries to contain the pandemic, the number of cases and COVID-19–related deaths is still increasing. Currently, more than 200 countries are affected by the pandemic.According to the WHO, up to May 2021, 157.7 million cases and approximately 3.2 million deaths from COVID-19 were recorded worldwide.–Considering the spatial distribution of cases, the use of geographic information systems (GIS) and spatial analysis techniques allows the mapping and identification of high-risk areas and assists health services in the planning and implementation of health measures to control the disease.Likewise, studies assessing the spatiotemporal patterns of COVID-19 have been developed extensively in Brazil.,The dispersion of COVID-19 has a heterogeneous dynamic across Brazilian regions. Regardless of the SARS-CoV-2 infection having the potential to reach all communities, some areas are noticeably more affected by virtue of the socioeconomic determinants and health services available.,Notably, Northeast Brazil has precarious socioeconomic indicators, such as a low municipal human development index (MHDI) and high social vulnerability index (SVI), with marked social disparity.We conducted an ecological and population-based study, using spatial and temporal techniques to assess the mortality and CFR due to COVID-19 in the municipalities of Northeast Brazil. The social vulnerability indicators of the municipalities were associated with data on mortality from COVID-19. The units of analysis were the populations from the 1,794 municipalities in this region. Herein, we analyze all deaths related to COVID-19 confirmed during the first year of the pandemic, from March 27, 2020 to March 27, 2021.,2); and a population of 57,071,654 inhabitants (the second most populous region in Brazil), which corresponds to approximately 30% of the Brazilian population. However, the highest demographic density occurs in the cities of the coastal strip of the region.Brazil is divided geographically into five regions: Midwest, South, Southeast, North, and Northeast.The epidemiological variables used in this study were as follows: 1) the absolute number of daily and monthly deaths from COVID-19 in the 1,794 municipalities of Northeast Brazil; 2) the mortality rate due to COVID-19. To calculate the mortality rate, we used the number of deaths from COVID-19 as the numerator and the corresponding population as the denominator. It was determined per 100,000 inhabitants; and 3) the CFR due to COVID-19. To calculate the lethality rate, we considered the total number of COVID-19–related deaths as a numerator and the total number of confirmed cases as the denominator. The result was multiplied by the constant of 100 and expressed as percentage (%).The SVI was also used. This estimates the degree of social vulnerability to which a population is exposed, being composed of three dimensions: urban infrastructure, human capital, and income and work. The SVI ranges from 0 to 1 and is classified as very low (0 to 0.200), low (0.201 to 0.300), medium (0.301 to 0.400), high (0.401 to 0.500), and very high (≥ 0.501).https://covid.saude.gov.br/). Population estimates for states and municipalities were collected from the Brazilian Institute of Geography and Statistics (IBGE) (https://www.ibge.gov.br/), considering the intercensus estimates for 2020. Social indicators (SVI) were collected from the Brazilian Social Vulnerability Atlas (http://ivs.ipea.gov.br/index.php/pt/). Finally, for spatial analysis, the digital cartographic grid of the Northeast region, divided by municipalities and in shapefile format, was obtained from the Geographic Projection System latitude/longitude .Data on COVID-19–related deaths were extracted from the surveillance database of the Brazilian Ministry of Health (R2). In addition, to describe the time trends, we calculated the monthly percentage changes (MPCs) and their respective 95% confidence intervals (CIs).P value of < 0.05 and their CI 95% did not include zero. Here, a positive and significant MPC value indicates an increasing trend; conversely, a negative and significant MPC indicates a decreasing trend, and nonsignificant trends are described as stable, regardless of MPC or AMPC values.Initially, we performed a descriptive analysis of the absolute number of deaths and the mortality rate for the Northeast region and states during the first 12 months of the pandemic. Next, to analyze the time trend of COVID-19–related deaths, we carried out a segmented log-linear regression model, using joinpoint regression models. The time trend of deaths from COVID-19 in the municipalities, classified according to the SVI and their respective subdomains, was also analyzed. The Monte Carlo permutation test was applied to select the best model for inflection points (with 999 permutations) and considering the highest residue determination coefficient  was calculated to identify areas with spatial dependence and their relationship with neighbors. From there, a scatter diagram was established with the following spatial quadrants: Q1 (high/high) and Q2 (low/low), which indicate municipalities with similar values to those of their neighbors and with positive spatial association; Q3 (high/low) and Q4 (low/high) indicate municipalities with different values from those of their neighbors, with no spatial association. Significant results were represented on Moran maps,,A retrospective space–time scan analysis was performed to identify high-risk clusters for COVID-19-related deaths, using the Poisson probability distribution model.P values of < 0.05 were obtained using 999 Monte Carlo simulations.Then, we ran the cluster analysis model, considering the following parameters: minimum aggregation time of 1 month, minimum of five deaths, no overlapping of clusters, circular clusters, maximum size of the spatial cluster of 10% of the population at risk, and maximum size of the temporal cluster of 50% of the study period.Microsoft Office Excel 2010 software  was used for data tabulation and descriptive analysis; Joinpoint Regression Program version 4.2.0  was applied for time-trend analysisHerein, we used public-domain aggregate secondary data and followed national and international ethical recommendations, as well as the rules of the Helsinki Convention. There was no way to identify the subjects; therefore, the use of informed consent was dispensed with. The project was approved by an ethics and research committee: CAAE n. 14384719.8.0000.5546.N = 14,667), Pernambuco , and Ceará . We observed that the peak of deaths occurred between May and August 2020 (the first wave of the pandemic) in all states, with a progressive reduction in the following months ; there was a decreasing trend between June and November 2020 ; and lastly, there was an increasing trend between November 2020 and March 2021 . Otherwise, when considering the total period (AMPC), seven states showed stable trends in mortality rate. Nevertheless, the states of Bahia  and Piauí , as well as the Northeast region , showed an increasing trend in this period.In addition to assessing the number of deaths, we also analyzed the time trends of COVID-19-related deaths in Northeast Brazil . InteresP = 0.03; N = 859 municipalities) and very high social vulnerability  had crude mortality rates of > 100 per 100,000 inhabitants. These rates were smoothed by the Local Empirical Bayesian Method, and the Moran global index showed significant spatial autocorrelation . Furthermore, we identified by LISA analysis the clusters of high risk of mortality formed by 224 municipalities, mostly on the coastline of the Northeast region: Bahia (N = 48), Sergipe (33), Piauí (19), Ceará (46), Paraíba (26), Pernambuco (25), Alagoas (5), Maranhão (6), and Rio Grande do Norte . On the other hand, the secondary cluster (March 2021) encompassed 458 municipalities in the states of Piauí, Pernambuco, Sergipe, and Bahia, with 3,340 deaths and an RR of 2.30 .Additionally, we identified two significant spatiotemporal clusters of COVID-19–related deaths in this Brazilian region  or between 2.5 and 5% . Notwithstanding, 84 municipalities (4.68%) had a CFR between 5 and 7.5%, and this rate was > 7.5% in 27 municipalities (1.5%). Moreover, concerning the CFR, the Moran global index showed significant spatial autocorrelation among municipalities . Correspondingly, the LISA Map showed that the municipalities with the highest CFR (N = 105) were located mainly in the states of Piauí, Ceará, Pernambuco, Alagoas, and Sergipe  can mask inequalities between populations. Therefore, further studies should implement techniques to evaluate clusters of cases while simultaneously adjusting for age and sex and other relevant covariates.Altogether, our analyses demonstrated municipalities with a high mortality and CFR due to COVID-19 in Northeast Brazil. Furthermore, increasing trends in deaths were observed particularly in municipalities with greater SVI. In addition, spatiotemporal analyses identified two high-risk clusters of deaths from COVID-19, mainly in municipalities on the coastal strip of the region, which are areas with the highest population density and tourism flows. Considering all this, we suggest that preventive strategies, such as implementing more restrictive measures to reduce social mobility, social and economic support by the federal government, and widespread vaccination of the population, should be implemented urgently to reduce the number of cases and deaths and avoid the collapse of the health system in Brazil.


Though numerous studies have focused on the cell wall disassembly of bananas during the ripening process, the modification of homogalacturonan (HG) during fruit development remains exclusive. To better understand the role of HGs in controlling banana fruit growth and ripening, RNA-Seq, qPCR, immunofluorescence labeling, and biochemical methods were employed to reveal their dynamic changes in banana peels during these processes. Most HG-modifying genes in banana peels showed a decline in expression during fruit development. Four polygalacturonase and three pectin acetylesterases showing higher expression levels at later developmental stages than earlier ones might be related to fruit expansion. Six out of the 10 top genes in the Core Enrichment Gene Set were HG degradation genes, and all were upregulated after softening, paralleled to the significant increase in HG degradation enzyme activities, decline in peel firmness, and the epitope levels of 2F4, CCRC-M38, JIM7, and LM18 antibodies. Most differentially expressed alpha-1,4-galacturonosyltransferases were upregulated by ethylene treatment, suggesting active HG biosynthesis during the fruit softening process. The epitope level of the CCRC-M38 antibody was positively correlated to the firmness of banana peel during fruit development and ripening. These results have provided new insights into the role of cell wall HGs in fruit development and ripening. Musa spp.) are one of the most important tropical fruits and food crops in the world. It is commonly harvested at the mature-green stage when the angularity on the fruit surface disappears. Banana is a typical climacteric fruit, and exogenous ethylene is usually used to artificially initiate fruit ripening prior to commercialization. During the ripening process, there is a burst of ethylene production coordinated with rapid softening-associated processes, including peel de-greening, peel, and pulp softening [Bananas  were significantly firmer than control ones and displayed a reduction in solubilization and depolymerization of polyuronides . HoweverIn the case of bananas, multiple studies have been performed to investigate the mechanism involved in banana fruit ripening at physiological, biochemical, and molecular levels during the past decades. Most studies have been focused on gene expression ,28,29,30Musa spp. AAA) at different developmental stages and the ripening process based on the whole-transcriptome gene expression analysis. In addition, an immunofluorescence labeling technique was employed to reveal the changes in the spatial and temporal distribution of different HG components in banana peels during developmental and ripening stages, besides the changes in pectin content and activities of key pectin degradation enzymes. The results will provide new insights into the role of cell wall HGs in banana fruit development and ripening.Though cell wall disassembly regard to banana softening has been extensively studied, little is known about cell wall construction during early fruit development. This study was to analyze the changes in HG-modifying genes in the peel of a Cavendish dwarf banana cultivar ‘Huanong Aijiao 1’ (The study was performed on fruits of 0 d (just emerging from the bunch), 35 d, 60 d, green matured , and yellow matured  fruits. The change in appearance is shown in To get an overview of molecular changes underlying banana fruit development, we have performed transcriptome profiling at its different developmental stages, as well as ripening. The numbers of differentially expressed genes (DEGs) between every two stages were shown in In total, there are 61 MaGAUTs, 64 MaPGs, 3 MaPGIs, 27 MaPMEs, 41 MaporPMEs, 47 MaPMEIs, 12 MaPAEs, and 18 MaPLs in banana Genome A.GAUT is the key gene family associated with the biosynthesis of HG. Nowadays, GAUT1, GAUT7, GAUT13/14 were proved to be involved in the biosynthesis of pectin HG. As shown in In total, 23 MaPGs showed differentially expressed levels during banana fruit development and 36 after ethylene treatment. Only four MaPGs  showed a higher expression level during the fruit developmental stages, while it was 16 for the ripening stage. The expression of two MaPGIs decreased with the development and was inhibited by ethylene treatment .All five MaPMEs differentially expressed during fruit development showed a decline in expression level. On the contrary, all four MaPMEs differentially expressed during fruit ripening were upregulated by ethylene treatment. Similar trends were observed with the expression of MaproPMEs, MaPLs, and MaPMEIs except for Ma08_g12230 (proPME) and Ma08_g12230 (PMEI) .Nine MaPAEs were differentially expressed during banana fruit development and ripening. Three of them  showed an increased expression level with the development of banana fruits, but a decreased one after ripening. On the contrary, the expression of Ma04_g18920 decreased with fruit development but increased after softening. Another three MaPAEs  were also induced by ethylene treatment, but the other two MaPAEs (Ma02_g20280 and Ma04_g18910) were downregulated during banana fruit development .To validate the results of the RNA-Seq analysis, the expression of 25 representative DEGs (one–six ones from each gene family) were analyzed by qPCR. The result indicated that it was consistent with the result from RNA-Seq .As shown in The pectin content in the peel of banana fruit at 0 d was 62.70 mg/g (dry weight). It decreased with the fruit development and reached the lowest level at harvest, which was significantly lower than that at 0 d. After ripening, it increased to 57.83 mg/g, which was at the same level as that at 35 d. The degree of pectin methylesterification (DM) of fruit peel at 0 d was the highest (59.07%) while the YM fruit showed the lowest one (47.60%), but no significant difference was observed with DM during fruit development and after ripening .N. It showed an increasing trend with the development of fruits and peaked at 60 d, followed by a decline thereafter. The peel firmness of GM fruits was at the same level as that of fruits at 0 d. However, the peel firmness of YM fruits was only 4.93 N, significantly lower than that of fruit peel at all the other stages.The changes in the firmness of fruit peel during development and ripening stages were also investigated. The rupture force of fruit peel at 0 d was 10.90 Ruthenium red (RR) was used to reveal the spatial and temporal changes of pectin in banana peels during fruit development after treatment of the section with NaOH. As shown in In the fruits at 0 d, the signal of banana PME antibody was nearly undetectable, with a relatively stronger one in the epidermic cells, cortex cells adjacent to it, and latex cells . No signThe JIM5 recognizes partially methyl-esterified HG (up to 40%), and this epitope was mainly present in the xylem vessel, the vascular bundles, and the epidermic cells of the peel at 0 d . The antThe JIM7 recognizing epitope is HG with a methylesterification degree of 40–80%. The signal of this antibody in the transverse section of banana peel at 0 d was also very weak, with a relatively higher level in the xylem vessel and the epidermic cells . The sigLM18 antibody recognizes lowly methyl-esterified HG, and its labeling pattern in the peel at 0 d was similar to that of JIM5, but with a relatively higher epitope level . The LM1No detectable signal was observed with CCRC-M34, CCRC-M130, and LM20 antibodies in banana peel (data not shown).p value of 0.012 during fruit development, 0.9611 with p value of 0.009 during fruit development and ripening stage. There was also a positive correlation between peel firmness and 2F4 intensity during fruit development .Because the epitope levels of 2F4, CCRC-M38, JIM7, and LM18 antibodies showed similar dynamic changes to peel firmness during banana fruit development and ripening. The correlation coefficient between them was analyzed. The coefficient between peel firmness and CCRC-M38 intensity was 0.9877 with Previous studies indicated that there were great differences in pectin content and the expression of HG-modifying genes between the peel and pulp during banana ripening ,14,42,43Fruit growth involves cell divisions and cell expansion resulting from a dynamic interplay between cell turgor pressure, cell wall biosynthesis, and degradation, as well as cell wall remodeling. It has been proposed that the cell wall component of fruit exocarp/peel controlled the expansion of the developing fruits and contributed to the final size and shape of the fruit ,45. HowePGIs, PMEs, proPMEs, and PLs, as well as most PGs, PMEIs, and PAEs in banana peels decreased during the fruit development. However, both biochemical and histological analyses revealed that the pectin content in banana peels decreased with fruit development, and there was a significant difference between banana peels at harvest and 0 d. This might be due to the down-regulation of GAUTs  in the meanwhile. On the other hand, four PGs  and three PAEs  showed higher expression level at later development stages than earlier ones. They might be related to the expansion of fruit and provide the flexible, extensible mechanical support that resists the strains resulting from the expansion of the underlying cortex tissue [Prunus persica) fruit [In the present study, the expression levels of all differentially expressed x tissue ,47. The a) fruit  and banaa) fruit ,48.The firmness of fruit peels increased significantly with the development of fruits and peaked at 60 d, followed by a decline at harvest. This decline in firmness of banana peel was suggested to be due to the significant increase in PL activity. Interestingly, the IF data revealed that the epitope levels of JIM7 and LM18 antibodies increased with the fruit development and peaked at harvest, while those of 2F4 and CCRC-M38 antibodies peaked at 60 d. In addition, there was a significantly positive correlation between peel firmness and the CCRC-M38/2F4 intensity during fruit development, suggesting that the content of fully de-esterified HG and unesterified/calcium ion cross-linked HG recognized by CCRC-M38/2F4 antibody, instead of pectin content and DM, was significantly correlated with the firmness of banana peel during fruit development. The increase in the antigen level recognized by the JIM7 antibody was also observed during the early development of tomato pericarp .Banana is a climacteric fruit. It is well known dramatic changes at physiological, biochemical, and molecular levels, including peel de-greening, fruit softening, and flavor change during the ripening stage, concomitantly with a burst of ethylene production and respiration, took place during the ripening stage of this type of fruits. Among them, the most apparent change is the reduction in fruit firmness. Cell wall disassembly is considered to be the major determinant of fruit softening during the ripening process in fleshy fruits ,51, whicMusa AAA cv. Brazilian were found to be upregulated after ripening via ethylene treatment [Over the last decades, the dynamic expression profiles of cell wall-modifying genes and corresponding changes in enzyme activities and cell wall composition revealed that pectin modification is primarily responsible for the progressive loss of firmness in ripening and withering fruits ,53,54. Ireatment . Howeverreatment ,15,38. Sreatment ,56,57,58MaGAUT7s, three MaGAUT1s, and two MaGAUT13/14s were differentially expressed during banana fruit ripening. Seven out of these 10 MaGAUTs were upregulated by ethylene treatment, suggesting there was still active biosynthesis of pectin HG during this process, which was in accordance with the observation in the ripening process of apple  [Nowadays, it is proved that GAUT1, 7, 13, and 14 are involved in the biosynthesis of HG ,59. In tmestica) .Consistent with the gene expression pattern, the activity of PG and PL in the peel of YM fruits was 2.25 and 6.60 times higher than that of GM fruits, respectively. Additionally, the PME activity also increased significantly from 13.09 to 21.10 in the present study. As a result, the fruit firmness decreased significantly after softening. Previous studies also found the activity of PG and/or PL in banana peels increased ,32,33, bPersea americana Mill.). In the present study, the firmness of banana peel decreased significantly after softening. However, both biochemical and histological analyses revealed that the YM fruits even contained higher levels of pectin than GM fruits, though a significant increase in activities of PME, PG, and PL was observed. This might be due to strong activity in HG biosynthesis taking place in the soft YM fruits. Similarly, the GalA content in the cell wall of apple also increased concomitant with a decrease in cell wall stiffness after being subjected to ultrasounds [Besides, at the molecular level, fruit cell walls also undergo extensive changes in structure and composition during fruit ripening, which results in the reduction in their mechanical strength. In the case of bananas, Duan et al.  suggesterasounds . These r2+ also could influence the formation of cross-linked pectin gels, and they both contribute to tissue firmness. In the present study, the HG components recognized by JIM7, CCRC-M38, and LM18 antibodies showed significantly lower levels in YM fruits than in GM fruits, and the intensity of 2F4 antibody recognizing un-esterified/Calcium ion cross-linked HG also decreased 20%. As mentioned above, the levels of these antigens showed the same trends as the firmness of banana peel during fruit development. Thus, the lower DM, lower levels of Ca2+ cross-linked HG, as well as unesterified or deesterified to partially methylesterified HG were contributed to the reduction in firmness of YM fruits.On the other hand, the pectin DM of YM fruit was lower than that of GM fruits, which might mainly result from the significant increase in PME activity. The removal of the methylesters from HG by PME during fruit development and ripening not only could facilitate PG action to increase cell wall porosity and decrease cell adhesion but also favor cell adhesion and the rigidity of the pectin network , and theMusa AAA, cv. Huanong Aijiao 1) at 0 d, 35 d, 60 d, and 85 d  were collected from the field at the same time when the daily average temperature is approximately 25 °C. The fruit peel was isolated and frozen completely in liquid N2 before storage at −80 °C till use. Additional GM fruit samples were kept at 18–22 °C and 100% of humidity after treatment with 500 μL/L of ethylene (40% v/w) to initiate ripening. Twenty-four hours later, the humidity was lowered to 80–90% while the temperature was kept the same. The fruit became soft, and the peel became yellow 6 d after ethylene treatment, namely YM fruits. These fruits were also sampled for analysis. Each treatment consisted of three biological replicates, each containing six fruit fingers from independent plants.The fruits of dwarf banana  according to the manufacturer’s instructions. The compression force is measured at the maximum peak of the force recorded on the graph and expressed in N.Fruit peel firmness was assayed using a texture analyzer | > 1 and a threshold of false discovery rate < 0.05 were used as the threshold to evaluate the significance of DEGs. GSEAPreranked was employed for gene set functional enrichment analysis [https://bigd.big.ac.cn/gsa/browse/CRA005631, accessed on 28 August 2021.RNA preparation, library preparation for RNA-Seq, and data analyses were carried out as described previously . In brieanalysis . Heatmapanalysis . All RNA−△△CT method. The primers used for qPCR are listed in Total RNA was extracted from the samples using the hot borate method described by Wan et al. , followew/v) polyvinylpyrrolidone followed incubation at 4 °C for 1 h with occasional stirring. The extracts were centrifuged at 15000 rpm for 30 min at 4 °C and the supernatant was collected to assay the activities of PME, PG, and PL.The extraction of the crude enzyme was adopted from the method described by Mirshekari et al.  with sli−1, at 30 °C and pH 6.5. PG activity was determined according to the modified method of Pathak and Sanwal [PME activity of the supernatant was determined using a modification of the method developed by Marcus and Schejter , exactlyd Sanwal : 100 μL d Sanwal . After td Sanwal . The actd Sanwal .v/v) at 70 °C for 30 min after homogenization. The pellet was crushed in liquid nitrogen and dried at 60 °C for 3 d. The determination of both pectin and methanol was carried out by the method described by Ma et al. [Measurement of pectin and methanol was based on the obtained alcohol-insoluble residue, which was prepared as described by Louvet et al.  with mina et al. . The DM The immuno-labeling of all antibodies was carried out exactly as described by Xu et al. , exceptfw/v)  in PBS buffer was used to stain de-methyl-esterified pectin. The sections were prepared, dewaxed in absolute ethanol, rehydrated in ethanol-PBS series, and washed in PBS for immuno-labeling fluorescence. RR was dropped onto the sections and kept at room temperature for 30 min. After rinsing in PBS 3 times, the sections were mounted in immersion oil  before observation with an Axio Imager D2 . To stain all pectin, the sections were first treated with 0.1 mol/L NaOH for 3 min before RR staining.RR  in the statistical program SPSS 19.0 for Windows . Three replicates were set for each treatment. Data are presented as the mean ± SE. Duncan’s multiple range tests are employed to evaluate multiple differences among means at a 5% probability level.We use the “cor.test” function in R (version 4) to calculate the correlation coefficient between banana fruit peel firmness and enzyme activity.Banana is one of the most important foods and fruit crops in the world. It is well-known plant cell walls play a very important role in fruit development and ripening. As a typical climacteric fruit, the disassembly of banana fruits during the ripening stage has been extensively studied. However, the associated information during banana fruit development and the organization of HG components in situ and their modification during the ripening process are unavailable.PMEs, proPMEs, PGIs, and PLs, most GAUTs, PGs, PMEIs, and PAEs in banana peel showed a decline in expression during the fruit development, concomitant to the relatively stable activities of HG degradation enzymes and pectin DM. Four MaPGs  and three MaPAEs  might be involved in the expansion of fruit peel during banana development. All the investigated HG-modifying gene families showed differential expression patterns after ethylene treatment except for the PGI gene family. Six out of 10 top genes in the Core Enrichment Gene Set belong to HG degradation genes, and all of them were upregulated after softening, paralleled to the significant increase in activities of HG degradation enzymes and decline in fruit firmness. Interestingly, active HG biosynthesis took place during the fruit ripening process. The lower DM, lower levels of Ca2+ cross-linked HG, as well as un-esterified or de-esterified to partially methyesterified HG might be related to the reduction in fruit firmness after softening. The content of fully de-esterified HG recognized by CCRC-M38 antibody, instead of total pectin content, was positively correlated with the firmness of banana peel during both development and ripening processes. These results suggested that the HG-modifying genes are collaborated in the expansion and growth of cells in banana peels during fruit development and played a key role in the disassembly of pectin polysaccharides in fruit ripening.In the present study, all differentially expressed