The proposed method involves converting the target element into an integer using a string hash function, followed by the conversion of said integer into a p-adic integer through algebraic properties. This process automatically establishes the topological tree access structure of the PSBF. The experiment involved a comparison of access performance among the standard bloom filter, dynamic bloom filter, and scalable bloom filter. The findings indicate that the PSBF offers advantages such as avoidance of a linear storage structure, enhanced efficiency in element insertion and query, improved storage space utilization, and reduced likelihood of false positives. Consequently, the PSBF presents a novel approach to the dynamic extensibility of bloom filters.Given the challenges associated with the dynamic expansion of the conventional bloom filter’s capacity, the prevalence of false positives, and the subpar access performance, this study employs the algebraic and topological characteristics of  V of a specific size m and multiple hash mapping functions H. The size of the bloom filter needs to be predetermined based on the number of data elements E to be stored and the desired probability of false positives, which poses challenges in accurately estimating the size of the stored elements in a system. The increase in false positives is observed in a bloom filter upon surpassing a specific threshold of stored elements. Fixed-size bloom filters are prone to significant storage space wastage or elevated false positives. Consequently, the expandability of bloom filters holds substantial research importance.The advent of contemporary information technologies, including big data, the Internet of Things, and cloud computing, has resulted in a substantial increase in data volume, posing significant challenges to computer systems in terms of data processing, storage, and retrieval. The bloom filter, a well-established probabilistic data structure, serves the purpose of determining the presence of a data element within a collection. This data structure offers notable advantages such as efficient space utilization and expedited query speed, rendering it extensively employed in various domains such as big data analysis , optimizTo address the aforementioned issues, previous studies have put forth over 60 enhanced bloom filters with the aim of enhancing their adaptability and performance . These eDespite the enhanced effectiveness of bloom filters in mitigating false positives, their ability to address computational overhead and additional space consumption remains limited. To tackle this issue, dynamic capacity expansion serves as a mechanism that facilitates automatic expansion of the bloom filter’s capacity in line with the growth of data volume. This approach not only significantly enhances the scalability of processing extensive datasets but also diminishes the rate of misjudgment. A robust dynamic expansion is crucial for enhancing the applicability of bloom filters and is a pivotal consideration in the development of extensive data processing systems.p-adic number serves as a valuable parameterization tool for computations within hyper-dimensional spaces );5.    end for6.  returnhashCode&0x7FFFFFFF7.  end function8.In the stage of inserting data elements, an element must first undergo mapping using a string hash function. The hash function employed in this study is BKDRHash , which ip-adic integers. The process commences with the establishment of an empty string “new_num_str”, designated for the storage of the converted outcome. Furthermore, the variables “reminder” and “reminder_string” are introduced to accommodate the retention of the residual value of the present bit and its corresponding string representation, correspondingly. Subsequently, the loop should be executed until the input integer “num” reaches 0, signifying the termination of the loop. Within each iteration, the remainder of the expanded prime number p divided by “num” should be obtained to determine the current bit’s remainder. It is imperative to ascertain whether the remainder falls within the range of 10 to 75. If it does, the corresponding character representation in the predefined mapping table “tenToAny” should be identified. Conversely, if the remainder does not fall within this range, it should be converted into a string representation. The resulting current bit string, “remainder_string”, should then be appended to the end of “new_num_str”. The prime number n is used to divide “num”, resulting in an updated value of “num”. Upon completion of the loop, the converted string representation of a p-adic integer is stored in “new_num_str” and returned.Algorithm 3 DecimalToAnyInput: num, pOutput: new_num_strfunction DecimalToAny1.new_num_str, remainder, remainder_string;2.  initialize variables whilenumdo3.  remaindernum mod p;4.    ifremainder > 9 andremainder < 76 then5.    remainder_stringtenToAny[remainder];6.      else7.    remainder_stringremainder);8.      end if9.    new_num_strtetany + remainder_string;10.    numnum/p;11.    end while12.   returnnew_num_str13.   end function14. Algorithm 3 delineates the sequential procedures entailed in the conversion of integers to 3-adic integers: 0.0001; 0.1001; 0.2001; and 0.0101. The specific steps for inserting these elements into the bloom filter are illustrated in PSBF element inserted. Let elements p-adic integer of the element p-adic integer of the elementp-adic integer storage of the elementAlgorithm 4 InsertElementInput: e, btOutput: newBtfunction InsterElement1.path, flag, num, newBt;2.  initialize variables fori⇐0 to len(e)—1 do3.  forh⇐0 to len(bt))—1 do4.    if string(e[i]) == bt[h].Id then5.      flag⇐true; 6.        if i =- 0 then7.        path⇐strconv.Itoa(h) + “.Index”8.          else9.        path⇐path + “.”+ strconv.Itoa(h) + “.Index”;10.          end if11.        bt⇐bt[h].Index;12.        break13.        else14.      flag⇐false;15.        end if16.      end for17.    if !flag then18.    if i == 0 then19.      a new node a of the tree, add a to the end of newBt, record path, and bt⇐newBt [len(newBt)-1].Index;20.       create else21.       a of the tree, add a to the end of bt, update newBt, and bt⇐bt [len(bt)-1].Index;22.       create a new node ifnum == 0 then23.         path⇐path + “.”+ strconv.Itoa(v) + “.Index”;24.          num++;25.          else26.         path⇐ path + “.0.Index”;27.          end if28.         end if29.        end if30.       end for31.   return s32.   end function33.The initial digit of the p remains consistent with the one used during the element storage process, and the integer resulting from the element mapping is expanded to derive the p-adic integer of the element. The detailed implementation of this process is presented in Algorithm 5.Algorithm 5 SearchElementInput: e, btOutput: true or falsefunction SearchElement1.to len(e)—1 doif len(bt) < 1 then3.    return false4.      end if5.    found⇐ false;6.    forh⇐0 to len(bt)—1 do7.    if string(e[i]) = bt[h].Id then8.      found⇐true;9.         bt⇐ bt[h].Index;10.       break11.       end if12.      end for13.    if !found then14.    return false15.      end if16.    end for17.   return true18.   end function19.The “SearchElement” algorithm, which is a component of the element query algorithm, bears a resemblance to the “InsertElement” algorithm. It employs the same hash function utilized in the stored procedure to convert the queried element into an integer. The selection of the expanded prime number p and hash functions were chosen for experimentation in this study.All experiments conducted in this study were performed within a consistent environment, utilizing the following main hardware configuration: Intel(R) Core(TM) i5-8250 U CPU @ 1.60 GHz, 1.80 GHz, and 12 GB RAM. The operating system employed wazs Windows 11 64-bit, and the programming language utilized was Golang 1.18.4. In order to achieve optimal performance of the PSBF, various prime numbers p that yields the optimal performance in a PSBF. p on the insertion and query capabilities of the bloom filter when inserting 1000 to 20,000 data elements. As the number of elements increases, both insertion and query times gradually rise, albeit with slight variations in the performance observed across different prime numbers p. In the context of insertion and query operations, the prime number p with a value of 31 demonstrated optimal performance and exhibited a brief execution time. Conversely, prime numbers such as 2, 3, 5, 7, etc., tended to exhibit a prolonged execution time, particularly when the number of elements was substantial, thereby resulting in a more pronounced degradation in performance. Consequently, this study advocates for the utilization of the expanded prime number p = 31 within the bloom filter as it yields superior performance and efficiency.For this study, the hash function’s output result length was set at 32, thus limiting the prime number p within the range of 2 to 31. The experiment employed a comparative analysis of insertion and query operations to determine the minimum prime number p-adic numbers in the PSBF, it becomes solely necessary to decompose the fixed-length integers into p-adic numbers based on the optimal prime number p. The PSBF does not internally utilize a hash function. In essence, the utilization of the PSBF does not necessitate the consideration of the number of elements or the dimensions of the bit array within the bloom filter. The selection of a suitable hash function for the PSBF pertains to the efficiency of operations performed on elements that are mapped to fixed-length sequences of integers.The determination of the most suitable number of hash functions for conventional bloom filters is contingent upon the quantity of inserted elements and the dimensions of the bit array employed by said filters . In contThe experiment involved the insertion and query of 1000–20,000 identical data elements using eight string hash functions, namely BKDRHash , APHash It is worth noting that the conventional bloom filter exhibits a false positive probability during member queries, wherein an element that is not present in the set is erroneously identified as being part of the set. Furthermore, the size of the bloom filter necessitates pre-definition based on the desired probability of false positives and the number of elements to be stored. Estimating the accurate size of the stored elements in a system poses a challenge. When the number of elements stored in a bloom filter exceeds a specific threshold, the occurrence of false positives will escalate. The utilization of fixed-size bloom filters will inevitably result in significant storage wastage or a high rate of false positives. To ascertain the superiority of the PSBF, this study undertakes a comparative analysis of insertion time, query time, space utilization rate, and misjudgment count in relation to standard bloom filters, scalable bloom filters , and dynRegarding the insertion operation, as depicted in In relation to space utilization, as depicted in p to convert the integer into a p-adic integer further. The depth d of the resulting bloom filter was determined based on the number of bits in the converted p-adic integer. The storage structure of the PSBF was transformed into a tree, deviating from the linear storage structure employed in current technologies. This modification enhances the efficiency of element insertion and query operations. Furthermore, the PSBF employs a selection process to determine the expanded prime number p based on the given integer, which is then utilized to convert the integer into a p-adic integer. Subsequently, the depth d of the bloom filter is determined based on the number of bits in the converted p-adic integer. This approach allows the PSBF to circumvent the need to consider the size of the bloom filter and the stored data, enabling automatic expansion of capacity and storage of any number of elements based on the storage elements. Consequently, the PSBF effectively utilizes the available storage space.This study employed the PSBF method to initially convert the target element into an integer, followed by the selection of an expanded prime number p by considering the integer obtained from the hash function, thereby minimizing false positives. When the p-adic integer depth of all data conversions was equal, it became possible to attain a probability of zero false positives.Based on the findings presented in As previously stated, the PSBF demonstrates clear advantages in terms of query time, space utilization, and number of misjudgments. It consistently exhibited shorter query times, better space utilization, and fewer misjudgments when compared to the scalable bloom filter, regardless of the size of the element set or the number of elements. Although the insertion operation time of the PSBF was slightly higher than that of the scalable bloom filter, in practical application scenarios, the insertion operation time of the bloom filter was typically significantly smaller than the query operation time. Consequently, the overall performance of the PSBF surpasses that of the scalable bloom filter.p-adic integers. The proposed approach offers improved efficiency in terms of element insertion and query operations. Moreover, it eliminates the need for parameter setting to accommodate capacity expansion, thereby mitigating space wastage and reducing the likelihood of false positives.To address the limitations of capacity in the existing bloom filter, it becomes unfeasible to reprocess extensive data for filtration. Moreover, when the data to be filtered approaches the upper limit of capacity during the reprocessing process, the false positive rate significantly rises, leading to a substantial decline in the efficacy of data filtration. Consequently, this gives rise to technical challenges that diminish the accuracy of the filtering process. This study introduced a bloom filter with an automatic expansion tree structure, utilizing the algebraic and topological properties of


As the incidence of prostate cancer (PCa) has increased, screening based on prostate-specific antigen (PSA) has become controversial due to the low specificity of PSA. Therefore, we investigated the diagnostic performance of prostate health index (PHI) density (PHID) for the detection of PCa and clinically significant PCa (csPCa) compared to PSA, PSA density (PSAD), and PHI as a triaging test. We retrospectively reviewed 306 men who underwent prostate biopsy for PSA levels of 2.5 to 10 ng/mL between January 2020 and April 2023. Of all cohorts, 86 (28.1%) and 48 (15.7%) men were diagnosed with PCa and csPCa, respectively. In ROC analysis, the highest AUC was identified for PHID (0.812), followed by PHI (0.791), PSAD (0.650), and PSA (0.571) for PCa. A similar trend was observed for csPCa: PHID (AUC 0.826), PHI (AUC 0.796), PSAD (AUC 0.671), and PSA (0.552). When the biopsy was restricted to men with a PHID ≥ 0.56, 26.5% of unnecessary biopsies could be avoided; however, 9.3% of PCa cases and one csPCa case (2.1%) remained undiagnosed. At approximately 90% sensitivity for csPCa, at the given cut-off values of PHI ≥ 36.4, and PHID ≥ 0.91, 48.7% and 49.3% of unnecessary biopsies could be avoided. In conclusion, PHID had a small advantage over PHI, about 3.6%, for the reduction in unnecessary biopsies for PCa. The PHID and PHI showed almost the same diagnostic performance for csPCa detection. PHID can be used as a triaging test in a clinical setting to pre-select the risk of PCa and csPCa. As the incidence of prostate cancer (PCa) has increased , PCa scrIn the past decade, the prostate health index (PHI) was introduced, and the Food and Drug Administration (FDA) approved the PHI for PCa in 2012 . PHI is p = 0.0013) but showed equal performance for csPCa ) and mean (standard deviation [SD]). Statistical differences were assessed using an independent Student’s p < 0.001) was smaller in men with PCa than that in the non-PCa group. As regards biomarkers, the total PSA level was similar between the two groups ; however, men with PCa had a significantly higher PSAD (0.14 vs. 0.17), PHI (33.5 vs. 51.4) and PHID (0.81 vs. 1.68) .The baseline characteristics of all cohorts are provided in p = 0.031), abnormal DRE , and PHI  were significant predictors of PCa. When prostate volume was combined with biomarkers, PSAD and PHID were also significant predictors of PCa . In addition, multivariate analysis adjusted for age and abnormal DRE revealed that the PSA level did not predict PCa (p = 0.317), but PSAD, PHI, and PHID were clinically significant predictors of PCa  (p = 0.176) and PSA level  were not significant predictors, but abnormal DRE  and PHI  were significantly associated with the prediction of csPCa. PSAD and PHID, which are biomarkers considering prostate volume, were also clinically significant predictors of csPCa . Similar to the results in PCa, when adjusted for age and abnormal DRE, PSAD, PHI, and PHID were clinically significant predictors of csPCa , but not PSA (p = 0.523)  . When an= 0.523) . The perp < 0.001) and PSA . However, AUC difference between PHID and PHI was not significant (p = 0.221). When csPCa was analyzed as an outcome, a similar order was observed: PHID (AUC 0.826), PHI (AUC 0.796), PSAD (AUC 0.671), and PSA (0.552)  and PSA . However, the AUC between PHID and PHI was not significantly different (p = 0.191).When applying ROC analysis to examine the ability of each diagnostic biomarker to detect PCa, the highest AUC was identified for PHID (AUC 0.812), followed by PHI (AUC 0.791), PSAD (AUC 0.650), and PSA (AUC 0.571) A. The AU (0.552) B. Similan =149) and PHID (n = 151), and the number of undiagnosed PCa remained the same (n = 14).Furthermore, when biomarker cut-offs that allowed for approximately 90% diagnostic sensitivity for csPCa were applied, PHI (55.4%) and PHID (56.2%) showed higher diagnostic specificity for csPCa than that shown by PSA (910.1%) or PSAD (20.9%). At cut-off values of PSA ≥ 3.26 ng/mL, PSAD ≥ 0.090, PHI ≥ 36.4, and PHID ≥ 0.91, 10.1%, 19.6%, 48.7%, and 49.3% of unnecessary biopsies could be avoided. There was little difference in the number of avoidable biopsies between PHI  and 48 (15.7%) patients were diagnosed with PCa and csPCa, respectively. We found that PHID showed the highest diagnostic performance for PCa and csPCa, and could reduce the number of unnecessary biopsies. In addition, when we categorized PHID according to different cut-off values, a positive correlation between the PHID cut-off and PCa or csPCa ratio was identified. Therefore, it could be used as a triaging test in a clinical setting to pre-select the risks of PCa and csPCa.In clinical practice, mpMRI is an essential tool, and its usefulness is gradually increasing in the diagnosis of PCa ,25. ParkThe PHI was developed to compensate for the limitations of PSA and was approved by the FDA for PCa in 2012. Le et al. reported the first study on the clinical utility of PHI in a prospective PCa screening study , in whicp = 0.013) [p = 0.221 and AUC 0.796, p = 0.191, respectively)In 2014, similar to the concept of PSAD, PHID was introduced . Tosoian= 0.013) . In cont= 0.013)  and PeteFurthermore, a consensus on the optimal PHID cut-off value is not available. Garrido et al. reported that when applying the biomarker cut-off that allowed for approximately 90% of diagnostic sensitivity for csPCa, 26.3% of unnecessary biopsies could be avoided at PHID ≥ 0.49 . In a stIn this study, when applying the biomarker cut-offs that allowed for approximately 90% of diagnostic sensitivity, the NPV of PHI and PHID was 89.2% and 90.0% for PCa, and 97.3% and 97.3% for csPCa, respectively. However, the PPV was relatively low at approximately 33.6–34.5% for PCa and 27.7–28.0% for csPCa, because it can be changed depending on the situation, such as the incidence of PCa. In our study, PCa and csPCa were identified in 28.1% (86/306) and 15.7% (48/306) of men, respectively, with serum PSA levels between 2.5 and 10 ng/mL. These real descriptors of the diagnostic test performance are expected to improve through machine learning in the future.This study had several limitations. First, an inherent selection bias may exist because of the retrospective design of this study, which was performed at a single institution. However, this study examined a prospectively collected database that reflected real-world clinical practices. Second, the sample size of the cohort was relatively limited; therefore, the diagnostic performance of each variable requires further validation with a larger cohort to corroborate the findings reported in the present study. Third, in our study, the prostate volume was estimated via TRUS using an ellipsoid formula. However, since some differences may occur depending on the method of measuring prostate volume, it should be taken into account when interpreting the diagnostic performance of PHID. Finally, we examined the outcomes of a cognitive-targeted biopsy combined with a 12-core systemic biopsy performed by an expert urologist; however, applying other biopsy methods might yield different results. Therefore, confirmation via a large prospective study is required to verify the results reported herein.In men with a PSA level between 2.5 and 10 ng/mL, PHI and PHID showed higher diagnostic performance for PCa and csPCa than PSA and PSAD. For the detection of PCa, the diagnostic performance of PHID was not significantly different from that of PHI. However, PHID had a small advantage over PHI, about 3.6%, for the reduction in the number of unnecessary biopsies. The PHID and PHI showed almost the same diagnostic performance for csPCa detection. We identified a positive correlation between the PHID cut-off and PCa or csPCa ratio. Therefore, it can be used as a triaging test in a clinical setting to pre-select the risk of PCa and csPCa and reduce the number of unnecessary tests while supplementing the shortcomings of PSA. Based on this study, further studies should be conducted to provide evidence that can more clearly predict the risk of PCa and csPCa through a combination of serum biomarkers and the result of mpMRI.


Acinetobacter infections have high rates of mortality due to an increasing incidence of infections by multidrug-resistant (MDR) and extensively-drug-resistant (XDR) strains. Therefore, new therapeutic strategies for the treatment of Acinetobacter infections are urgently needed. Acinetobacter spp. are Gram-negative coccobacilli that are obligate aerobes and can utilize a wide variety of carbon sources. Acinetobacter baumannii is the main cause of Acinetobacter infections, and recent work has identified multiple strategies A. baumannii uses to acquire nutrients and replicate in the face of host nutrient restriction. Some host nutrient sources also serve antimicrobial and immunomodulatory functions. Hence, understanding Acinetobacter metabolism during infection may provide new insights into novel infection control measures. In this review, we focus on the role of metabolism during infection and in resistance to antibiotics and other antimicrobial agents and discuss the possibility that metabolism may be exploited to identify novel targets to treat Acinetobacter infections. Acinetobacter spp. are a major cause of opportunistic infections. Acinetobacter spp. are Gram-negative coccobacilli that are nonfermentative, oxidase negative, indole negative, catalase positive, and lack flagella but are capable of twitching motility  and increasing extensively-drug-resistant (XDR) strains. A. baumannii can infect any site in the body and is a frequent cause of urinary tract infections, bloodstream infections, and ventilator-associated pneumonia in critically ill patients, contributing to increased morbidity and mortality  for development of novel antibiotics  and insertion sequencing (INseq) have shown that metabolic genes are essential during infection. Nutrient acquisition and metabolism were major contributors to A. baumannii infection and persistence in a murine model of lung infection and a Galleria mellonella model of infection  was first described in 1911 and was isolated in minimal medium with either acetate or quinate as the carbon source  cycle, the glyoxylate pathway, and gluconeogenesis in central carbon metabolism  (Acinetobacter spp. that can utilize glucose as a carbon source use the following pathway: (i) glucose is oxidized by a nonspecific pyrroloquinoline quinone (PQQ)-dependent aldose dehydrogenase that produces gluconolactone, (ii) gluconolactone is enzymatically or nonenzymatically hydrolyzed to gluconate, and (iii) gluconate is phosphorylated and enters the Entner-Doudoroff pathway  . Acineto pathway . A smallactivity . However-glucose , 46. The-glucose . The rolAcinetobacter spp. also notably degrade many organic compounds by dissimilatory pathways. Environmental strains such as Acinetobacter baylyi ADP1 are well studied for their ability to oxidize aromatic compounds by the β-ketoadipate pathway and potential for bioengineering , cAMP, and enzyme IIA of the glucose-specific PTS system (Acinetobacter spp. encode a catabolite repressor protein (Crp) homolog that is a major target of persulfidation in the presence of exogenous sulfide stress  protein that represses aromatic compound degradation in the presence of organic acids such as succinate and acetate by multiple mechanisms, including transcription-independent mechanisms  system. The manganese import protein MumT is required for lung infection and dissemination to the liver in mice; however, MumT is not required in calprotectin-deficient mice , and murine lung infection  system, which contributes to intrinsic antibiotic resistance (–mlaFA. baumannii ATCC 17978UN strain uncovered synthetic interactions between isoprenoid biosynthesis and the Mla system in A. baumannii that promote virulence and resistance to antibiotics and host stresses (A. baumannii lipid synthesis and metabolism are important for virulence.All colistin  98–100)–100Aciner organs . A. baumsistance –105. In stresses . TherefoA. baumannii β-oxidation helps resist, suggesting A. baumannii may metabolize the toxic PUFAs  such as arachidonic acid (AA) and decosahexaenoic acid (DHA) are released during inflammatory bursts of macrophages and neutrophils –109. PUF–ic PUFAs . Monounsormation . In addiaumannii , 113.A. baumannii can use fatty acids directly in membrane biogenesis or as a carbon source or energy sources. Phospholipids are a major component of the Gram-negative bacterial cell envelope and are synthesized by phosphatidylglycerol phosphate (PGP) phosphatases. In A. bauamnnii, two PGP enzymes, PGPA and PGPB, have been identified  phospholipid species and increased susceptibility to gentamicin , hexanoate , and pyruvate  was described in a 1987 study by Bouvet and Grimont as part of a biotyping scheme of clinical Acinetobacter isolates . T. TA. bauin vitro . A hutH nfection . The Hutnfection , 130. Hunfection . The autree zinc . The mulreceptor , 131–133ptor 131–.A. baumannii to change its transcriptional program to persist and adapt to a hostile host environment. Consistent with this paradigm, multiple transcriptional regulators have been identified that link Acinetobacter amino acid metabolism and virulence. For example, A. baumannii cysteine regulators Cbl and GigC have been shown to be important for virulence in a G. mellonella model of infection , putrescine, and other amine compounds as carbon sources  clade, and it is not present in nonpathogenic Acinetobacter spp. (P. aeruginosa, the level of kynurenine intermediate 3-OH-anthranilate was increased in bronchial alveolar lavage fluid at 12 and 24 h postinfection and depended upon an intact P. aeruginosa kynurenine pathway (P. aeruginosa has also been shown to promote its survival in the presence of human neutrophils by inhibiting reactive oxygen species production (A. baumannii kynurenine catabolism affects virulence and the immune response has yet to be determined. Overall, pathogenic Acinetobacter spp. appear to have evolved strategies to utilize host amine compounds as carbon and nitrogen sources, and future work may investigate whether these pathways affect immune cell function and modulate the host-pathogen interaction.In addition to using amino acids directly as carbon and nitrogen sources, some  sources , 36. CarAci01347 . GABA ise stress . Urea ise stress . Recentln source . Interester spp. . Host ceter spp. , 150. In pathway . Kynurenoduction . WhetherAcinetobacter strains use to acquire nutrients in the host during infection. However, many open questions remain as to Acinetobacter nutrient acquisition and metabolism during infection. Pathogenic Acinetobacter spp. can degrade numerous amino acids and other amines as carbon sources, but their roles as nitrogen sources are less characterized. Similarly, sulfur acquisition is largely unexplored. Sulfate assimilation was found to be critical for persistence in a G. mellonella model of infection (Acinetobacter spp. encode additional mechanisms to liberate host-specific sulfur sources, as described for other bacterial pathogens (Acinetobacter spp. acquire cofactors, amino acids, nucleotides, and additional nutrient metals from specific host niches.In conclusion, recent work has identified numerous metabolic strategies nfection . It is uathogens . SimilarA. baumannii clinical isolates from the 1950s, which replicate extracellularly during infection. Recent studies have shown that some modern A. baumannii clinical isolates are capable of replicating intracellularly in macrophages or epithelial cells (A. baumannii acquires nutrients to sustain its metabolic demands is unknown. Additionally, many studies suggest that A. baumannii asymptomatic colonization of multiple body sites is associated with infection risk (8––Acinetobacter spp. use to survive as a commensal, including nutrient utilization. In a mouse model, thioredoxin-mediated reduction of secretory IgA promoted A. baumannii gut colonization (A. baumannii with upper respiratory tract microbiota species and found that A. baumannii inhibits commensal bacteria with acinetobactin (Acinetobacter calcoaceticus features that allow it to thrive in the gastrointestinal tract and identified relevant acid resistance, salt resistance, and nutritional flexibility (Acinetobacter bacteria in the gut was positively correlated with meat consumption in adults with nonalcoholic hepatic steatosis (A. baumannii regulates carbon source utilization by carbon catabolite repression in the complex milieu of nutrients in the host is unknown and likely shapes infection outcomes.Many of the mechanistic studies described here were conducted using al cells . Nutrienn risk 8––16, 146.nization . As menttobactin . Anotherxibility . Abundanteatosis , suggestA. baumannii iron acquisition has been successfully targeted by the new antibiotic cefiderocol, illustrating the potential for essential nutrient acquisition pathways to be targeted for new therapeutics. However, cefiderocol resistance has already been identified in carbapenem-resistant A. baumannii, and therefore new therapeutics must be developed. Multiple studies have implicated the pentose phosphate pathway in the response to polymixin antibiotics that target the outer membrane (Acinetobacter metabolism may be able to successfully synergize with existing antimicrobials and the host immune system. Targeting nutrient acquisition or metabolism would likely be effective against both hospital-acquired and community-acquired strains, a key benefit to this strategy. A better understanding of how nutrients modulate the host-pathogen interface during Acinetobacter infection may uncover new avenues to solve the problem of antimicrobial resistance.membrane , 157, su


To accurately measure ultrathin Descemet stripping automated endothelial keratoplasty (DSAEK) donor lamella thickness during the first postoperative year and to correlate this with pre-operative and other postoperative measurements.Donor lamella thickness in 41 eyes undergoing DSAEK for Fuchs endothelial dystrophy (FED) was measured using the Tomey Casia OCT directly after graft preparation and at 1 week and 1, 3, 6 and 12 months postoperatively. Visual acuity and endothelial cell density were measured as the secondary parameters.Individual graft thickness profiles were shown to be fairly regular within the optically relevant area. There was a strong and highly significant correlation between the pre- and postoperative lamellar thicknesses at all time points (p < 0.0001). Compared with the measurements directly after preparation at the cornea bank, the lamella thickness decreased by 12% after 12 months. Between 1 and 12 months postoperatively, the lamella thickness (mean ± SD) changed from 112 ± 27 μm to 101 ± 21 μm. Best spectacle-corrected visual acuity (BSCVA) changed from 0.46 ± 0.30 logMAR pre-operatively through 0.36 ± 0.33 at 1 month to 0.13 ± 0.16 at 1 year postoperatively. The endothelial cell counts were comparable to those reported in previous studies.Thickness profiles of individual grafts were fairly regular within the optically relevant area. A strong relationship between pre- and postoperative graft thicknesses was detected, and ultrathin DSAEK grafts prepared using methods similar to that applied in this study are expected to show a deswelling of around 12% during the first postoperative year. No correlation was detected between graft thickness and BSCVA. Posterior lamellar keratoplasty (PLK) is currently the most frequently performed surgical technique for treating corneal endothelial cell dysfunction, predominantly caused by Fuchs endothelial dystrophy (FED) and pseudophakic bullous keratopathy. Compared to penetrating keratoplasty, PLK leads to better refractive results, with a faster recovery and improved safety , 2. CurrWhile the donor lamellae for DSAEK were initially prepared by manual dissection, the introduction of an automated microkeratome for graft preparation  providedFor more than a decade, eye banks have stepped in to help surgeons with graft preparation of equally good quality , leadingThe aim of this prospective study was to investigate the relationship between pre- and postoperative posterior lamellar graft thickness in ultrathin DSAEK corneal grafts in subjects with FED and to evaluate postoperative deswelling. Pre-operatively and during 12 months after surgery the graft thickness was measured with the same anterior segment optical coherence tomography (AS-OCT) device. The secondary objectives of this study were to measure endothelial cells and study the relationship between graft thickness and visual outcome .For this study, patients with FED and a visual acuity (VA) of < 0.6 (Snellen) were included. All subjects underwent ultrathin DSAEK at the Rotterdam Eye Hospital between May 2017 and July 2018. Exclusion criteria were previous keratoplasty in the included eye, severe progressive glaucoma , history of retinal or glaucoma surgery, age-related macular disease, amblyopia, nystagmus, expected postoperative VA < 0.6 (Snellen), corneal neovascularization > 1 quadrant, or an indication for a tissue-typed graft. Ethical approval was waived by the Medical Ethical Committee of the Erasmus Medical Center, Rotterdam because the Dutch Medical Research Involving Humans Act (WMO) did not apply . This study adhered to the tenets of the Declaration of Helsinki. All the participants provided written informed consent.All precut donor grafts were prepared in the same eye bank . The method of graft preparation and storage was described by Pels and Rijneveld . After eThe four cornea surgeons at the Rotterdam Eye Hospital performed all ultrathin DSAEK surgeries. After removal of the anterior cap and meticulous centering, the central donor graft was trephined with the endothelial side up using a vacuum donor cornea punch  with a diameter of 7–8 mm (depending on donor and recipient cornea metrics). A superior 4.5 mm scleral tunnel was made in the recipient’s eye, and before opening the complete wound, a 7.5–8.5 mm descemetorhexis was performed using a Price hook  with the aid of air in the anterior chamber. A disposable type 2 Tan Endoglide™  and a Tan forceps were used to insert the donor tissue. After 10 min of complete air filling of the anterior chamber, an air bubble of approximately the same diameter as that of the graft was left to keep the donor in place. Whenever possible, the marking made by the eye bank to indicate the cutting direction on the donor cornea was oriented horizontally in the recipient’s eye. Postoperatively, the patients were kept in the supine position for 3 h before they were discharged from the hospital.After surgery, patients were prescribed dexamethasone (0.1%) eye drops  six times a day for the first month, four times a day for the following two months, and then tapered to one time daily at 12 months. Ofloxacin eye drops were administered 3 times daily for a maximum of 4 weeks.Assessments were conducted pre-operatively and at 1, 4, 13, 26 and 52 weeks after surgery. Corneal images were acquired pre-operatively, with the posterior lamella still in situ, at the ETB-BISLIFE, Cornea Department, and postoperatively at our hospital using the same type of anterior segment (AS) OCT . Images (16 mm x 16 mm) were acquired in both 2D and 3D modes . When the auto-alignment function indicated good alignment, three consecutive scans were performed. A scan for which the central reflective beam was visible on all images, warranting perpendicular recording, was used for the analysis.One week postoperatively, only OCT images were recorded. From the first month postoperative onward, the following measurements were performed: AS-OCT, BSCVA , and endothelial imaging using specular microscopy . The best endothelial image was selected by observation for analysis with custom-made software . ParticiData were collected in Castor EDC  and analyzed using Microsoft Excel (2010) and IBM SPSS Statistics for Windows, version 23 .As the pre- and postoperative  graft orientations may not be identical, 16 radial corneal images were used to construct a circular lamellar thickness profile of 32 values at 2 mm from the center: one profile from the pre-operative measurements and the other from the initial postoperative examination. Using cross-correlation, the angle of rotation for an optimal match of both profiles was determined for each graft.For longitudinal analysis of the lamellar thickness, only two (matched) radial images were used, which were (arbitrarily) denoted as the ‘horizontal’ and ‘vertical’ profile respectively; each profile comprising 5 lamellar thickness values .For analytical purposes, the pre-operatively obtained Snellen VA was converted to logMAR values. Regression analysis was performed to examine the relationship between the pre- and postoperative lamellar thickness and between lamellar thickness and visual acuity.The VFQ-39-NL scores were recoded, and the composite outcome was calculated . BecauseWe included 47 eyes of 47 patients with Fuchs endothelial dysfunction in this study.Due to missing data, particularly on pre-operative lamellar thickness, 6 patients were excluded from the analysis. The baseline characteristics are presented in Table The radial thickness profiles  of all 41 pre-operative posterior lamellae are shown in Fig. The longitudinal postoperative results with respect to central lamellar thickness (CLT), VA and ECD are summarized in Table CLT was examined separately for grafts that had required rebubbling and for those that had not. The former decreased from a mean thickness of 135 ± 23 μm at baseline to 119 ± 25 μm at the end of follow-up, for the latter CLT was reduced from 111 ± 21 μm to 98 ± 19 μm; the difference at baseline being statistically significant  and at 52 weeks being not (P = 0.09).During the entire follow-up period, ECD decreased, and VA improved. No significant correlation was observed between VA and lamellar thickness at any of the visits during follow-up visits -DSAEK and to analyze the correlations between pre-and postoperative graft thickness measurements.Measurements of the posterior lamella with the aid of Casia OCT proved to be reproducible, and after correction for variations in rotational positioning of the grafts (see Methods) measurement positions at the donor tissue bank and postoperative measurements were matched. Compared to the pre-operative values, the thickness showed a steep increase at 1 week postoperatively. At one month, the lamellar thickness was slightly lower than the pre-operative values  studies ; the impThe thickness profiles of the individual grafts appeared to be fairly constant within the optically relevant area. In this prospective study, measuring pre-and postoperative ultrathin DSAEK graft thickness with the same type of OCT and using a strict measuring protocol, we demonstrated a strong relationship between pre-and postoperative graft thicknesses. It can be expected that such grafts will show a deswelling of approximately 12% during the first postoperative year compared to the thickness measurements directly after preparation.


Background and Objectives: The aim of this study is to investigate the femoral tunnel geometry  on three-dimensional (3D) computed tomography (CT) and graft inclination on magnetic resonance imaging (MRI) after anatomic anterior cruciate ligament (ACL) reconstruction using a flexible reamer system. Materials and Methods: A total of 60 patients who underwent anatomical ACL reconstruction (ACLR) using a flexible reamer system were retrospectively reviewed. One day after the ACLR procedure was performed, all patients underwent three-dimensional computed tomography (3D-CT) and magnetic resonance imaging (MRI). The femoral tunnel location, femoral graft bending angle, femoral tunnel length, and graft inclination were assessed. Results: In the 3D-CTs, the femoral tunnel was located at 29.7 ± 4.4% in the posterior to anterior  direction and at 24.1 ± 5.9% in the proximal to distal (high to low) direction. The mean femoral graft bending angle was 113.9 ± 5.7°, and the mean femoral tunnel length was 35.2 ± 3.1 mm. Posterior wall breakage was observed in five patients (8.3%). In the MRIs, the mean coronal graft inclination was 69.2 ± 4.7°, and the mean sagittal graft inclination was 52.4 ± 4.6°. The results of this study demonstrated that a comparable femoral graft bending angle and longer femoral tunnel length were observed compared with the reported outcomes from previous studies that used the rigid reamer system. Conclusions: ACLR using a flexible reamer system allowed for an anatomic femoral tunnel location and a comparable graft inclination to that of the native ACL. In addition, it achieved a tolerable femoral graft bending angle and femoral tunnel length. Of the various surgical methods used for anatomical anterior cruciate ligament (ACL) reconstruction (ACLR), femoral drilling methods that are independent of the tibial tunnel have garnered attention ,2,3. TheA flexible reamer system was developed to overcome the limitation of the transportal technique that uses the existing rigid reamer system. Because the femoral drilling in this system is performed without more than 120° of knee hyperflexion, securing the surgical field, a relatively long femoral tunnel can be generated . This caBecause the postoperative outcomes of ACLR are affected by not only the graft length within the tunnel but also the femoral graft bending angle and graft inclination angle, merely securing a long femoral tunnel is not sufficient to obtain a desirable outcome. It is known that the femoral graft bending angle affects graft stress within the femoral tunnel, leading to tunnel widening or graft failure when an acute graft bending angle is formed ,18,19. AHowever, there has not been a comprehensive analytical study on femoral tunnel geometry and graft inclination after ACLR using a flexible reamer system. Therefore, the aim of the current study as a case series is to investigate the femoral tunnel geometry  on three-dimensional (3D) computed tomography (CT) and graft inclination on magnetic resonance imaging (MRI) after anatomic ACLR using a flexible reamer system. It was hypothesized that ACLR using a flexible reamer system would result in an anatomical femoral tunnel location and an average femoral tunnel length of 35 mm or more while maintaining a tolerable graft bending angle. In addition, it was hypothesized that it would provide a relatively native graft inclination.n = 3), multiligament injury for which combined ligament reconstruction was performed (n = 1), and no follow-up MRI (n = 1). Finally, 60 patients were enrolled in this study. This retrospective investigation was conducted following approval from the Ethics Committee of Konkuk University Medical Center (KUMC 2023-01-001).The medical records, 3D CT images, and MRI scans of 65 patients who underwent anatomical ACLR using a flexible reamer system at our institute from September 2021 to June 2022 were retrospectively reviewed. The inclusion criteria were primary ACLR; single-bundle reconstruction; the use of a soft-tissue graft; and availability to attend 3D CT and MRI evaluations. The exclusion criteria were selective bundle reconstruction, multiple-ligament injury, and revision ACLR. Among the 65 patients, 5 were excluded due to revision ACLR (All procedures were performed by a single experienced surgeon (DWL) using a flexible reamer system . In all patients, soft-tissue grafts  were used, the diameters of which were 8–9 mm. The diameters of the femoral and tibial tunnels were equal to the diameter of the graft.Three portals were created using a 30° arthroscope . The antThe ACL femoral attachment was removed to identify the bony landmarks  while preserving the remnant tissue substantially using electrocautery . While visualizing through the AL portal, the center of the femoral tunnel was marked inferior to the lateral intercondylar ridge and just behind the bifurcate ridge using a microfracture awl through the AAM portal, with the knee in 90° of flexion A. The tuOne day after the ACLR procedure was performed, all patients underwent 3D CT scans . During the examination, the knee was extended as fully as possible.To assess the femoral tunnel location, a true medial view of the lateral femoral condyle with the image of the medial femoral condyle erased at the center of the intercondylar notch was obtained. The quadrant methods used previously by Bernard et al.  and ForsThe 3D CT scans were imported into 3D software  for the assessments of the femoral graft bending angle and femoral tunnel length. The femoral graft bending angle was defined as the angle formed by the longitudinal axis of the femoral tunnel and the line connecting the intra-articular aperture of the tibial tunnel and the intra-articular aperture of the femoral tunnel . The femOne day after ACLR, all patients underwent MRI with a 3.0-T system apparatus  to evaluate for graft inclination. The graft inclination on the coronal plane was defined as the angle between the medial margin of the ACL graft through more than one slice and a line parallel to the tibial plateau at the level of the middle of the medial collateral ligament A. BecausThe statistical analysis was performed using SPSS software . Intrarater reliability was assessed using the intraclass correlation coefficient (ICC) with the following classifications: excellent (>0.9), good (0.75–0.9), moderate (0.5–0.75), and poor (<0.5). Interrater reliability between the examiners was assessed using kappa (k) values and classified as excellent (0.81–1.00), substantial (0.61–0.80), moderate (0.41–0.60), fair (0.21–0.40), or slight (0–0.20) . All radThe basic demographics of enrolled patients are summarized in Regarding the femoral tunnel location, it was located at 29.7 ± 4.4% in the posterior to anterior  direction and at 24.1 ± 5.9% in the proximal to distal (high to low) direction. The mean femoral graft bending angle was 113.9 ± 5.7°, and the mean femoral tunnel length was 35.2 ± 3.1 mm . There wThere were no cases of iatrogenic chondral damage of the medial femoral condyle during the procedure. The mean operative time was 72.4 ± 12.1 min.The results of this study were compared with those of previous studies in which an anatomical single-bundle ACLR using a flexible reamer system or rigid reamer system was performed .The most substantial findings of the current study were that the flexible reamer system allowed for an anatomic femoral tunnel location and a comparable graft inclination to those of the native ACL. In addition, our results demonstrate that a comparable femoral graft bending angle and longer femoral tunnel length were observed compared with the reported outcomes from previous studies that used the rigid reamer system .Parkar et al.  publishep = 0.01) and coronal (p < 0.01) inclinations. Hagiwara et al. [In terms of graft inclination, Jamsher et al.  applied a et al.  reportedRegarding the femoral graft bending angle, there are contradictory reports between the rigid reamer system and the flexible reamer system. Seo et al.  reportedn = 25) and one in the rigid reamer group (n = 25) [The mean femoral tunnel length (35.2 ± 3.1 mm) of the present study was longer than that of the rigid reamer system and similar to that of previous studies that used the flexible reamer system . An adva(n = 25) . HoweverBy analyzing 3D CT and MRI performed in previous studies, the present study investigated not only femoral tunnel geometry but also graft inclination. To date, there have been no reports of the long-term clinical effects of flexible reamers. Since this study generated tunnels using anatomic femoral footprints with the application of the flexible reamer system and was able to reproduce graft inclination close to native ACL, it should be considered significant, allowing the expectation of desirable long-term clinical outcomes.This study is a comprehensive evaluation of 3D CT and MRI after ACLR in a relatively homogeneous group of 60 patients at a single institution. Based on the study results, when using a flexible reamer, it is possible to create an anatomically consistent femoral tunnel within a short surgery time, and because the graft bending angle is not acute, we believe that satisfactory radiological examination results, such as CT and MRI, can be obtained once one becomes familiar with this technique.The current study had some limitations. First, this study was retrospective in design, and there was no control group. Second, since few studies have investigated the femoral tunnel geometry of ACLR, studies comparable to the radiological results of this study and their results have been insufficient. The reason for analyzing previous studies in the results is solely to supplement the data analysis of previous research, which may be insufficient in a case series. Third, this study did not assess the heterogeneity of the patient’s characteristics and the risk of bias in the included papers. Fourth, no clinical outcomes were included because this study analyzed 3D CT and MRI data right after surgery. Therefore, even a satisfactory radiological outcome should not be predicated on desirable clinical outcomes. Further research is needed on this. Fifth, while the femoral graft bending angle can be changed depending on the knee motion, this study evaluated the patients only in static states by CT, so it has a limitation in evaluating in vivo clinical significance. Finally, at least 1 year of postoperational MRI follow-up is required to evaluate the effect of the femoral geometry and graft inclination on graft maturation.ACLR using a flexible reamer system allowed for an anatomic femoral tunnel location and a comparable graft inclination to that of the native ACL. In addition, it achieved a tolerable femoral graft bending angle and femoral tunnel length.


In acoustic surveys, the main parameter determining the resolution of sampling along a transect is the distance between successive echosounder transmissions or “pings”. An increase in either the time interval between pings or the speed of the vessel increases the inter-ping distance, hence decreasing the effective sampling resolution. This study investigated whether a loss in along-transect resolution affects the mean backscattered acoustic energy, leading to uncertainty and/or bias in abundance estimates. To this end, a real acoustic survey was echo-integrated, followed by the application of a systematic resampling scheme to simulate a decrease in pinging resolution. For each transect, the mean backscattered acoustic energy calculated at each resolution was compared with that at the original resolution. Transects were characterised according to their heterogeneity and spatial autocorrelation to investigate their effect on the relationship between abundance error and sampling resolution. Uncertainty was seen to increase with decreasing resolution, with higher heterogeneity and lower spatial autocorrelation accelerating the rise in imprecision. Although the mean bias across replicates was zero, the asymmetry of the bias distributions increased with decreasing resolution, leading to an increasing probability and magnitude of underestimation ( It combines acoustic data collected by active sonar with biological sampling to quantify the density of different fish and nekton species. In trawl-acoustic campaigns, an oceanographic or fishing vessel navigates a portion of the ocean or a lake, describing straight trajectories or transects4 until it covers a fraction of the region of interest that is considered representative of the entire area. As the survey progresses, the vessel records acoustic data using a down-looking echosounder, intermittently interrupting the survey to conduct fishing trawls to identify the species present and determine their size distribution. The abundance of fish in a given area, 5 . In this paper, the focus is only on the along-transect resolution, considering that the other two  resolutions are fixed.One of the main advantages of acoustic surveys is that they provide relatively intensive sampling in both the vertical and horizontal directions. For the down-looking echosounders used in trawl-acoustic surveys, sampling in the vertical direction is exhaustive up to the extinction range of the acoustic signal, with a sampling resolution that depends on the sampling rate of the echosounder’s analog-to-digital converter , which in narrowband acoustics can vary from millimetres to tens of centimetres depending on the pulse duration and configuration usednce Fig. , which iing Fig. . The bal9) thereby increasing the distance between consecutive pings. On the other hand, autonomous vehicles often move slower, resulting in samples taken closer together.The change in the vessel speed directly affects how closely the samples are taken for a given ping interval. If the vessel is faster, there will be more distance between consecutive samples, and if it is slower, the samples will be closer together. While the typical trawl-acoustic surveys use vessel speeds around 10 kn, some so-called “surveys of opportunity” use faster fishing or merchant vessels (up to 14 kn or even more10). In addition, the ping interval can be increased for two other important reasons: alternate pinging and increased sampling range. First, alternate pinging involves distributing pings from various sensors into different groups to avoid interference and crosstalk11. Recently, it has gained importance due to the commercialization of a generation of wideband echosounders12, which has raised the risk of crosstalk due to the enlarged bandwidth of individual sensors. Second, increasing the sampling range increases the ping interval, as it takes longer for the sound to travel a given distance and return. It has also recently gained importance owing to renewed interest in the exploitation of mesopelagic populations and their role in transporting carbon in the ecosystem13 following a re-estimation of their abundance14. This has led some acoustic surveys previously targeting epi-pelagic species to increase their sampling range from ~ 200 m  to ~ 1000 m to include mesopelagic species, multiplying the minimum ping distance requirement by a factor of ~ 5 while maintaining the same vessel speed.During acoustic sampling, the ping interval can be modified to accommodate changes in the distance to the seafloor and to avoid aliased seabed echoes  in the Bay of Biscay8. This particular year was chosen because of the relatively high along-transect resolution used in comparison with the subsequent years when the sampling range was increased to include mesopelagic species among the acoustic targets. Acoustic data covered 1240 km from 54 different transects or transect segments with an average length of ~ 23 km and an average ping interval of ~ 0.5 s , when fish schools were aggregated in the water column or near the seabed. Acoustic data were recorded with an average ping interval of 0.5 s, vessel speed of 10 kn (5 m/s), and pulse duration of 1 ms , following a systematic sampling design of uniformly spaced (28 km between transects) parallel transects perpendicular to the coast .Data were collected from the 28 m long research vessel Emma Bardán using downward looking echosounders  mounted on the ship’s hull. In situ on-axis calibration of the echosounders was performed prior to the survey using the standard target methodologyast Fig. . The watThe main objective of the analysis was to measure the influence of sampling resolution on the acoustic-based abundances. As in the trawl-acoustic methodology abundance is estimated using Eq. , for simn times to each transect for each ping distance, and then the mean NASC was calculated for each of the n sets of data generated at each simulated ping distance to determine the uncertainty and bias , each considered as an independent measurement. For each transect, the dispersion and bias of the NASC resampled values were then analysed in terms of the simulated ping resolution, as well as the heterogeneity and spatial autocorrelation characteristics of the acoustic data. The basic measure used for ping resolution was the distance between pings or “ping distance”, entclass1pt{minimaThe key to this work was to realistically simulate the decrease in ping resolution that can occur in an acoustic campaign  through computer resampling techniques. To achieve this without distorting the underlying spatial structure of the data, systematic resampling was performed within each transect. Systematic  means that resampling is carried out in an orderly and chronological manner, with resampling locations homogeneously distributed at constant intervals Fig. . This isAn initial problem faced with this systematic resampling scheme was that, because it consisted of removing some of the available pings, the possible combination of pings to be removed varied with the resampling resolution. As a result, for some resolutions, there were not enough repetitions, resulting in resampling sets of unbalanced size, making it difficult to determine whether some of the observed uncertainty was due to the loss of sampling resolution per se or to the lack of sufficient repetitions. To overcome this problem, a linear interpolation of the original data was performed within each transect (using the "approach" function of R), which allowed to perform systematic resampling using any possible ping distance. In order to obtain a sufficiently large number of samples from which to make statistical inferences, random transect origin delays (up to 30 s) were applied in each replicate to achieve variability, and 3000 resampling repetitions were performed at each ping distance Fig. . Using t23. The resulting resampling distributions were examined by constructing statistical metrics to infer the average precision and bias for each transect and for every ping distance in the sequence.Each replicate of systematic resampling resulted in a measure of mean acoustic density per transect. These sets of 3000 mean values per transect and ping distance were then treated as bootstrap samples24). Therefore, to realistically simulate an acoustic survey, the mean abundance per transect was estimated in two steps: first, the mean NASC values were calculated for each of the 1-nmi EDSUs, and then they were averaged over the transects. The 1-ping NASCs were used to simulate the reduction in resolution, and the intermediate 1-nmi NASC means were used to obtain results comparable to those of typical surveys.While acoustic backscatter was echo-integrated at the highest available along-transect resolution (1 ping), echo-integration in acoustic surveys is usually performed using lower along-transect resolution cells, defined by the Elementary Distance Sampling Unit (EDSU), which is often chosen as 1 nmi  and transect (t) was also obtained for each ping distance (r):t) for each ping resolution (r) were then obtained by averaging Similarly to Eq. , when eaentclass1pt{minimat) and ping resolution, r represents each resampling repetition, The mean NASC per transect (t) for each ping resolution (r), and A central assumption in this study is that the abundance estimated with the original pinging resolution of 2.5 m was correct. Two types of error were examined for each transect and ping resolution: (1) the dispersion of the distribution of resampled abundances and (2) the deviation of these resampled abundances from those obtained with the original ping interval (assumed true). The dispersion, t) and ping resolution. To study bias, the deviation, t), ping resolution (r) as follows:t) for each ping resolution (r), and r is the replicate and n is the number of replicates. The modal deviation was the most frequent value of each distribution, and the probability of underestimation was calculated as the ratio of the number of negative deviations to the total number of bootstrapped replicates for each transect and ping resolution.Finally, the coefficient of variation per transect, Finally, to simulate the effect of EDSU lengths different than 1 nmi on the error calculations, the bias was assumed invariant and, according to the Central Limit Theorem, the variance levels were assumed to be proportional to the number of samples, hence estimating the change in To help explain the variation in abundance dispersion and bias with sampling resolution, a set of characteristics of the acoustic data per transect were selected. Mean acoustic characteristics per transect were calculated in three broad groups that were considered to have a potential impact in abundance accuracy: fish aggregation typology, heterogeneity and spatial structure.25. Heterogeneity was chosen to represent the extreme value content of each transect, because of the importance of these values, which was reflected in a preliminary analysis of the data  according to inequality of their income distribution. The Gini index is bounded between 0 and 1, with a value of 0 for perfect equality and a value of 1 for perfect inequality. The index is based on the Lorenz curve Fig. , a grapho 1 Fig. .For each transect, the heterogeneity values were calculated at the original, maximum ping resolution, and then averaged per EDSU of 1 nmi. However, as heterogeneity is likely to change its value with resolution, the Gini values were also calculated for all ping resolution distances in the sequence. This was done to study the evolution of heterogeneity with the ping resolution and to infer, in the case of calculating a Gini for a lower sampling resolution, what the equivalent Gini would have been if calculated at the 2.5 m resolution used in this study.28. Geostatistical analysis is based on the semi-variogram of the data (variogram for short), which is used to plot the variability between data points as a function of their mutual distance  for each transect  is low and if the correlation range is small compared with the region dimension, the estimation variance is expected to be large. Conversely, a large sill and correlation range should result in low variance. Consequently, a proxy for the spatial autocorrelation structure, Sample variograms Fig.  were derect Fig. . A proxy31) was applied to the acoustic backscattering echograms, using Movies + version 4.4, to obtain fish aggregation typologies32. The school processing consists of an image segmentation process applied to the echograms to detect and isolate the echotraces corresponding to each individual aggregation to obtain its morphological characteristics35. Average aggregation characteristics per transect were then obtained  were constructed, using the different characteristics of the acoustic data in each transect as auxiliary variables. However, as preliminary results indicated that morphological aggregation characteristics provided less explanatory power than heterogeneity and spatial autocorrelation Table , and in 36) regression models were fitted to the scatterplots to obtain predictions of the statistical descriptors as a function of ping resolution, with heterogeneity and autocorrelation as auxiliary variables.Bootstrapped distributions of resampled deviation values were plotted for each ping resolution and heterogeneity and correlation level. Several statistical descriptors were then provided to summarise the bootstrapped distributions. Uncertainty CV, mean and modal deviation, as well as the probability of underestimation were used to summarise the resulting deviation distributions and were plotted against ping resolution. Linear and non-linear  and spatial autocorrelation (Corr) were grouped into three bins, each containing 4–6 transects, and were included in the regression models as categorical variables. The categorical bins for heterogeneity were constructed as follows: low–Gini ≤ 0.4; mid–0.4 < Gini ≤ 0.6; high–Gini > 0.6. And the bins for spatial autocorrelation were as follows: low–Corr ≤ 0.33; mid–0.33 < Corr ≤ 0.66; high–Corr > 0.66. Linear and GAM models were compared using the Akaike Information Criteria (AIC).https://shiny.rstudio.com/) was developed to incorporate the main model results of the resampling exercise and provide more flexible predictions. The application allowed to increase the level of detail and flexibility of the plots, adding the possibility to switch between two of the available heterogeneity indices and to consider EDSU values other than 1 nmi.An interactive application based on Shiny  theWhen the scatterplots were segregated by level of heterogeneity and spatial structure, new patterns emerged. The NASC deviation values against ping resolution were observed to increase faster with higher heterogeneity  and lower spatial autocorrelation levels Fig. , being tThe bootstrapped distributions of the deviation values for different heterogeneity levels and ping resolutions Fig.  support https://aztigps.shinyapps.io/PingRateStudio/). Increasing the EDSU values reduced the uncertainty levels for any sampling resolution.Concerning the different heterogeneity indices shown in the interactive application provided as an alternative to Fig. Finally, the probability of underestimation exhibited a particular pattern with the ping resolution. For small ping distances, the probability of underestimation was low and increased with the ping distance, reaching 50% at ~ 12.5 m and stabilising at ~ 30 m Fig. . This maThe decrease in AIC when covariates were added demonstrated their usefulness in capturing the change in uncertainty with ping resolution. Both the heterogeneity and spatial structure were significant covariates Table . In term16, which predicts an increase in variance as the number of independent samples used for estimation decreases. This result is also in qualitative agreement with previous empirical results in acoustic surveys40, where precision was found to be positively correlated with the fraction of volume effectively sampled. However, these previous papers focused on resolution across transects, with along-transect resolution considered to be continuous. Here, it is shown that the resolution along the transect affects the uncertainty of the acoustic abundances .Another novelty of this study is that, in addition to analysing uncertainties in the estimates , it also analyses bias, i.e. potential systematic deviations from the true abundance. To deepen in the understanding of the estimation bias, the bootstrapped distributions of NASC deviations Fig.  were sumMore interestingly, however, despite the expected overall unbiasedness, there were consistent asymmetric trends in the variability Fig.  that ledThis behaviour can be explained by the skewed distribution of fisheries acoustic data, which contains many very small and a few extremely large values Fig. . In this42, there is usually only one opportunity to conduct the acoustic sampling, due to budget and time constraints43. In the case of a unique opportunity to sample the area, the most likely outcome of a poor sampling is a somewhat underestimated abundance, that is, in the “short term”, the poorly sampled abundance tends to be underestimated. Furthermore, the trend in the modal deviation from the resampled values shows that the most likely underestimation level increases with ping distance.However, if missing extreme values favours underestimation, one might wonder why the mean deviation is zero, even in the worst resolution sampling scheme. In other words, why there is no contradiction between Fig. 45. It should be noted that these typical rare extreme values found in acoustic data are not outliers, but rather perfectly valid values that occur naturally in any fishery campaign due to the contagious nature of fish populations25. The skewed nature of the acoustic data observed in this study is well known by the fisheries acoustics community and consistent with previous observations of fish density data17.Abundance estimation therefore relies on the detection of extreme values, which, due to their scarcity, act as a population of “rare species”. For these rare populations, abundance estimates can be distorted by their low detection probability, often leading to biased estimatesTwo explanatory variables, heterogeneity and spatial autocorrelation, were included to assess their influence on the increase in uncertainty at low resolution. Heterogeneity was measured using inequality metrics, in particular the Gini index. This variable was used to provide information on the importance of extreme values in a given dataset. The results of the resampling exercise showed that the degree of heterogeneity of the acoustic data had a significant effect on the relationship between both random and systematic errors and ping resolution Table . On the 30. This was accounted for in the definition of the spatial autocorrelation index, which includes not only the sill proportion but also the range proportion in its calculation  resampling method applied is believed to have reproduced the way in which the ping resolution is reduced in real acoustic surveys by increasing the ping interval or vessel speed, thus preserving the spatial autocorrelation of the fisheries acoustic data. The method used to obtain the averages per transect was consistent with that used in real trawl-acoustic surveys by including the intermediate step of calculating the mean abundances per EDSU . Consequently, the understanding gained of the effect of reducing the along-transect resolution on precision and bias should be reliable and generally applicable to many real acoustic surveys .This analysis was based on acoustic data collected during a real trawl-acoustic surveyThe resampling scheme applied, including the previous interpolation step Fig. , allowed3, the application should be straightforward for each transect segment associated with a given reference haul. This could also be applied to larger homogenous strata containing many transects or to entire surveys, as the general trends would be valid, and it could be useful to compare different surveys or make interannual comparisons of the same survey. However, the estimated errors should be considered as relative rather than absolute (as will be discussed below).This analysis was carried out at the level of transects or transect segments of approximately 23 km in mean length, each assigned to a single species composition. Therefore, if applied to an acoustic survey where species attribution is performed using a “reference haul” approachSince the Gini index increases with the ping distance Fig. , when apThere are some other considerations in this study that should be noted. Perhaps the most important limitation is the large variability in the resampling results. Even though the trends in uncertainty and bias were clear and stable across the different transects, there was a large variability in the trends obtained, probably in part because of the different values registered on each transect Figs.  and  8. This can also be applied to the categorical variables used. Although heterogeneity and autocorrelation levels generally control the rate of precision loss and underestimation, when more than three categories are included, there may be inverted or constant trends in the intermediate values (not shown). Therefore, heterogeneity indices improve predictions Table , especiaThe acoustic survey used as the basis for the resampling analysis was recorded using a 7° beamwidth transducer. Therefore, strictly speaking, the results obtained are only valid for this type of transducer. However, in an attempt to provide some insight into the potential effect of different beamwidths on the results, the sampled fraction of the along-transect plane Fig.  was calcThis study only tested the purely statistical effect of a reduced sampling rate on the average acoustic backscatter. It was not measured the potential incidence of the reduced resolution on the appearance of acoustic aggregations on the echograms, and the potential effect this might have had on the assessment through the scrutiny process.This study focused on studying a survey applying trawl-acoustic methodology using vertical transducers installed on a mobile platform traversing an area. Some of the assumptions associated with this methodology entail sampling at a speed higher than the average swimming speed of the target species. Therefore, potential biases due to non-compliance with this requirement were not addressed in this investigation. Furthermore, the analysis carried out was completely spatially oriented and the considerations derived from the study pertain to the spatial resolution of the sampling within the target area. Consequently, deducing the possible consequences of increasing the ping interval for a stationary platform would be challenging and out of the scope of this study, as it would involve discussing temporal rather than spatial sampling and resolution, subject to a completely different set of assumptions.8; therefore, even if it was not possible to cover the full range of possible ping distances, the study should be able to reflect and inform about typical and realistic conditions encountered in actual acoustic surveys.Finally, this study assumes that the abundance estimate obtained using the original, minimum ping-distance resolution is accurate. The average ping distance used in the survey was 2.65 m and ranged from 1.05 m to 3.7 m, with standard deviation of 0.85 m. The sampling intensity used is consistent with that typically applied in acoustic-based assessment surveysBased on these considerations, the main value of this study lies in its explanatory power. It should be reliable in describing the general effect of poor along-transect sampling on the error of abundance estimates, but the predictions of the actual errors should be considered relative, as the level of increased dispersion and underestimation will depend on the particular level of the large values detected. However, even if the predicted error levels are relative, the general trends observed are robust. It is therefore worth noting the change in trend that occurs at ping intervals of ~ 12.5 m for any category of heterogeneity and autocorrelation. Below this interval, although the simulation predicts slightly overestimated results, the level of overestimation is generally close to zero. Beyond ~ 12.5 m, however, the predictions are often underestimated, and here the level of underestimation becomes noticeable. Therefore, this ~ 12.5 m interval could be taken as an easy-to-remember safety threshold, beyond which areas of potentially biased abundance estimation are reached. Considering the typical speed of sound in seawater (and ignoring possible processing or synchronisation delays in the acoustic equipment), this would lead to maximum ranges of over 1800 m, which is sufficient to completely cover the entire epi- and meso-pelagic zones .Maurolicus muelleri), the most abundant and accessible mesopelagic species in the Bay of Biscay. Based on the results obtained, the applied increase in recording range resulted in a longer ping interval (of approximately 1 s), resulting in ping distances of approximately 5 m, which placed the along-transect resolution well within the safety margin described above. Consequently, the campaign was continued with the extended ping interval without any additional measures.The origin of this analysis was the concern about the increase in the maximum sampling distance in the JUVENA campaign. In this campaign, starting in 2015, the recording range was increased from 250 to 500 m in order to estimate the abundance of pearlside (The consequences of a reduced resolution along the transect for acoustic-based abundances are an increase in uncertainty and an increase in the probability and magnitude of underestimation caused by the highly skewed distribution of acoustic data, where the mean values are heavily influenced by a few extreme values. High heterogeneity and low spatial autocorrelation accelerate the increase in uncertainty and underestimation levels with decreasing resolution.Supplementary Information.


A Sorghum flour (SF) is a leading and prominent food source for humans in African countries. Recently extensive studies have been conducted on Sorghum bread (SB) or sorghum composite bread (SCB), covering various aspects. However, there are many technical challenges in the formation of SF and sorghum composite flour (SCF) that impact the quality of the bread and fail to meet the consumer’s desires and expectations. This review primarily focuses on the characteristics of SF, SCF, SB, and SCB, with discussions encompassing the rheological and morphological properties of the dough, improvement strategies, and bread quality. Moreover, a comprehensive analysis has been conducted to investigate the behavior of SF and SCF along with a discussion of the challenges affecting bread quality and the strategies applied for improvement. The significant demand for nutrients-rich and gluten-free bread indicates that sorghum will become one of the most vital crops worldwide. However, further comprehensive research is highly demanded and necessary for an in-depth understanding of the key features of SF and the resulting bread quality. Such understanding is vital to optimize the utilization of sorghum grain in large-scale bread production. Sorghum bicolor L. Moench) belongs to the grass family. In 2023, the global production of sorghum is projected to reach approximately 60.06 million metric tons, according to the United States department of agriculture (USDA) [Sorghum grain (e (USDA) . Sorghume (USDA) . Sorghume (USDA) . Furthere (USDA) . (2) Bine (USDA) ,8. (3) Fe (USDA) . Sorghume (USDA) .The integration of sorghum in the bread industry has gained remarkable attention in food industry research. Several factors contribute to the increased utilization of sorghum in the bread industry. Firstly, the gluten-free nature of sorghum enables the production of gluten-free bread ,11. Due Usually, the method employed to modify SF involves the addition of hydrocolloids, including starch, gums, protein, etc. . MoreoveFew reviews have discussed the properties of SF and SFC and their role in the baking industry, including the treatments used to improve the final product. Also, certain earlier reviews discussed processing techniques for sorghum-based products in general. This includes SB as well as its relationship with glycemic and antioxidant responses ,25. In gThis section explains the characteristics of SF and SCF, and the challenges encountered when forming dough. In the next section, the problems of SB and SCB were discussed in terms of color, flavor, volume, and consumer acceptance, and then passing through the section on flour improvement strategies, this section highlights the improvement of flour in turn to produce bread optimally.Studying the technical characteristics, including the rheological properties of SF and SCF, contribute to understanding the problems of making bread to improve technical and nutritional aspects. Therefore, many researchers investigated the rheological and other techniques properties of SF and SCF dough, such as pasting, rebound, deformation, creep and creep recovery, etc. ,27,28,29Rheological tests are among the most practical approaches for determining quality and texture indications in food items. Dough rheological characteristics define how it may deform, flow, or rupture when stressed and might be utilized in choosing and specifying suitable materials. Understanding the essential rheological characteristics of any dough can provide insight into how the dough will behave in different processing conditions.Dynamic rheometry has been used extensively to explain the rheological characteristics of food substances, such as doughs, which provides data regarding the flow and elastic characteristics of materials. The sample for dynamic measurements is typically sandwiched between two circular plates. The system is kept at the desired temperature while applying sinusoidal stretching with various frequencies . The spePasting characteristics indicate the changes that take place in the flour when applied heat while present water . PastingAs for the pasting properties of SF without other flour, an increase in the breakdown viscosity was indicated. For instance, when measuring the pasting properties of Zimbabwean SF (Macia) using the Viscograph-E device, the breakdown viscosity is very high (760.00 BU) compared with wheat flour (724.00 BU) . With thThe Farinograph is used to measure the shear and viscosity of a dough mixture (flour and water) to provide important information about dough, such as dough viscosity, water absorption, and flour stability. The absence of gluten protein in sorghum decreases water absorption and dough development time . It was Some treatments for SF, such as extrusion, can lead to increased water absorption and dough growth for the SCF. For example, extrusion of SF at 110 °C and 160 °C with humidity of 10%, 14%, and 18% and mixing it with wheat flour in a ratio of 10:90 sorghum wheat increased water absorption and growth time of compound dough while decreasing dough stability . The incMorphological properties such as scanning electron microscopy SEM, confocal laser scanning microscopy CLSM, etc., can contribute to understanding the properties of SF and SCF dough, including particle shape, size, and surface characteristics, as well as the distribution of associated proteins with starch granules. This information can be useful in developing and optimizing food products that incorporate SF and SCF ,50,51. T−1 protein being present, respectively [The extended vacuum observed in the starch granules of heat-treated SF in the previous statement is believed to have been created by the water-annealing of starch in a granule in conjunction with high pressure of hot water vapor at the hilum. This process can lead to changes in the morphology and properties of the starch granules, as mentioned earlier. Confocal images of the starch granules labelled with the fluorescent protein plumb-line (CBQCA) in ectively .SEM can provide a comprehensive picture of the state of starch granules and fiber in SF and SCF dough, as well as any changes that may occur due to processing. For example, SEM has been used to compare the morphology of starch granules in native flour or dough versus those in processed flour or dough that have undergone different treatments, such as extrusion or grinding with planetary balls. In one study, SEM was used to examine the effect of grinding with planetary balls on the morphology of starch granules in SF. The images showed that highly treated samples had significantly smaller starch granules and fewer large particles than the untreated sample. Additionally, the images showed that endosperm pieces, fiber particles, starch granules, and protein bodies formed a conglomerate . GrindinX-ray diffraction (XRD) is a nondestructive technique used to analyze the crystalline structure of materials, including flour. XRD works by passing X-rays through a sample and measuring the angles and intensities of the resulting diffracted X-rays. The pattern of diffracted X-rays can be used to determine the crystal structure of the material . In the It is common to use X-ray diffraction to characterize the properties of SF and sorghum starch, whether they are native or treated. X-ray diffraction has been applied to modified SF and sorghum starch through soaking, dry heat, heat-moisture, extrusion, or chemical treatments such as acid lamination, oxidation, and acetylation ,51,54,55The XRD pattern revealed significant differences between the modified starch and the native starch, indicating that the modifications had altered the crystalline structure of the starch . SimilarSB has become a topic of interest now. It is also gluten-free because of its many benefits and contains high levels of phenolic compounds and antioxidants. On the contrary, antinutritional elements in SF, including enzyme inhibitors, tannins, phytate, or protein crosslinkers, are responsible for reducing protein digestibility . DespiteSourdough bread (SDB), flatbread, kissra bread, khamir bread, and frybread are among the various bread types of sorghum ,60,61,62Color is one of the essential factors in determining bread quality because it is one of the first characteristics that draw the consumer’s attention. The bread color measurement refers to measuring the colors of the surface and crumbs. There is no significant difference in the color of SB with different hybrids, but some flour treatments can change the color of the bread; this is what we will discuss later ,72. On tThe volume of regular SB is low compared with the size of wheat flour bread due to the gluten content of wheat flour, allowing it to absorb water (retaining softness and flexibility for a longer period). Good gluten can retain gases, which provide the bread the desired porosity and spongy characteristics ,14,75. TThe highest proportions of SF mixed with wheat flour were (30% and 40%). It was observed that there was a reduction in the effects on the elasticity of the breadcrumbs, in addition to a reduction in the size of the bread ,74,77. TMicrobial decomposition, texture loss, and off-flavor development are all factors that contribute to the rapid deterioration of bread flavor and smell during storage. For many years, the topic of bread flavor has been ignored, but it is now emerging as a critical feature in the baking sector. It should be mentioned that the perception of bread flavor includes a wide range of characteristics like aroma, taste, warmth, appearance, and mechanical eating features, all of which contribute to customer satisfaction. Aroma is a crucial element in food acceptance, and it is mainly connected with volatile compounds that trigger olfactory receptors in the nasal canals. In contrast, taste is produced in response to active taste receptors in the presence of nonvolatile substances. The flavor of SB is related to the quality and method of treatment of SF ,74. The An organoleptic examination of a bread’s texture complex, in terms of its mechanical features, is known as a texture profile analysis that measures chewiness, adhesiveness, springiness, resilience, cohesiveness, and firmness. The TPA hardness values for the breadcrumbs made with SF vary depending on the type of SF used. Studies have shown that this variation in hardness values is observed in hybrid sorghum bread, where white SB is harder than red SB . The harIn the previous sections of this review, we discussed excerpts from SF improvement techniques. In this part, we explore in detail these techniques that include external additives  and some SF treatments such as extrusion, dry-heat, microwave, heat-moisture, and fermentation. Hydrocolloids are one of the most popular external additives to improve the properties of SF. It can be described as a group of food ingredients, primarily polysaccharides, and some proteins frequently used in various food products. The functional qualities of hydrocolloids in food are incredibly diverse, such as stabilizing, emulsifying, thickening, gelling, and regulating the formation of sugar and ice crystals. However, the two primary functions for which hydrocolloids most frequently used are thickening and gelling. Examples of primary hydrocolloids include starch, guar gum, locust bean gum, xanthan gum, carboxymethyl cellulose, and gum arabic .Recently, several studies focused on using colloids in sorghum instead of gluten to improve its rheological properties. Xanthan gum is one of the most popular colloids used in dough improvement, is a polysaccharide that can form a gel-like structure in water, which can help improve the dough’s structure and texture. In one study, xanthan gum was added at 0.5% and 1% on SF combined with wheat flour in a 90% wheat:10% sorghum ratio. The results showed that adding xanthan gum positively affected the properties of composite flour and bread, producing a stronger dough . HoweverStarch is a carbohydrate consisting of glucose units linked together by glycosidic bonds. The starch powder mainly comprises branched amylopectin and helical and linear amylose. Amylopectin and amylose constitute about 98–99% of the dry weight of the starch. Starch is available in food grains , one of the cereals’ most significant nutritional components ,112,113.Adding starch to SF as a flour blend can significantly impact bread quality, particularly its size or volume. Studies have shown that adding rice starch to sorghum flour at a proportion of 10% as flour, along with other colloids such as tapioca starch with 3% HPMC (Hydroxypropyl methylcellulose), potato starch with 4% xanthan, and rice starch with 3% xanthan, can increase the size of the loaves compared with loaves made with 100% cornmeal. When the proportion of rice starch was increased to 20% and 30%, no further change in loaf size was observed . The visWeissella cibaria MG1, it was observed that adding 10–20% of the enriched dough can lead to an increase in the viscosity of the dough and a lower complex modulus G*, indicating a softer and more elastic texture in the resulting bread [Dextran can be defined as a bacterial exopolysaccharide (EPS) or a complex glucan in the form of chains of varying length linked together by α-1,6 glycosidic linkages between glucose monomers, from which α-1,3 linkages are branched . Lactic ng bread .Weissella confusa A16 on modifying the flavor and texture of sorghum-wheat composite dough was observed. Compared with the original bread, sorghum-wheat composite dough enriched with dextran produced in situ can produce soft, high moisture, and foldable bread [Moreover, the magnificent effect of dextran produced in situ by le bread . This wale bread . Figure A microwave is a device that uses electromagnetic radiation in a specific frequency range to heat materials. It is considered one of the most efficient heating devices because it can heat materials quickly and efficiently . The mec3 led to a decrease in the pasting properties of SF, including a decrease in breakdown viscosity, peak viscosity, pasting viscosity, and setback. This may be due to the effect of microwave roasting on the starch granules in the grain, which can result in changes in the structure and properties of the starch [On the other hand, roasting sorghum grain by microwave can decrease the breakdown viscosity, peak viscosity, pasting viscosity, and setback. A study found that roasting sorghum grain by microwave at 778 to 546 kg/me starch . Moreovee starch . This die starch ,131.Regarding dry heat treatment, it is considered scarcely used in flour processing, and the oven is often used to conduct it. Dry heat treatment of sorghum grain can be used along with particle size distribution. Some functional properties, such as water absorption capacity and increasing fat and fiber, were found to be related to the approximate composition of the flour, whereas moisture, protein, solubility index, ash, water holding capacity, and foam were not. On the other hand, heating SF at 125 °C for 30 min increased the volume of bread produced from heat-modified flour compared with control bread, and the consumer acceptance score was 5.05 for heat-treated bread and 4.76 for native control bread . This ca2) and the moisture of the crumbs, as well as an increase in the redness of the bread. Moreover, the peel color and crumbs change to more red and yellow (a*) and (b*), respectively, while the (L*) would be light. This might be attributed to occur of the Maillard reaction, which results from the interaction between amino acids and free sugar  anThe heat-moisture processing can change the physical and chemical properties of starch by inactivating the starch crystals. Thus, it leads to an increase in the crystallization of starch, as well as its effect on solubility and rebound viscosity . For exaVarious types of fermentation can be used to enhance SF or to produce bread and gluten-free bread. Lactic acid bacteria (LAB) and baker’s yeast are among the most common types of fermentation used in the production of SB and SCB or to enhance SF and SCF ,141,142.L. reuteri and W. cibaria in the fermentation of SF, along with the addition of 10% or 20% of the fermented dough, can lead to the formation of exopolysaccharides (EPS) during fermentation. EPS are complex carbohydrates that are produced by certain microorganisms during fermentation and can have a significant impact on the texture and quality of the final product. In this case, the formation of EPS during fermentation may contribute to a decrease in the elasticity and strength of the dough. This is because EPS can interfere with the development of gluten in the dough, which is responsible for its elasticity and strength. Additionally, EPS can also increase the water-holding capacity of the dough, which can further contribute to a decrease in its overall strength [2. Thus, it leads to the production of bread with softer crumbs and increases the shelf life of bread [Weysella that exhibit mild acidification are utilized [Weissella confusa A16 strain (dextran produced in situ) led to a significant increase in the pliable, moist, firm, soft, elastic, and smooth compared with sorghum dough or native SCB [Weissella cibaria MG1 to ferment buckwheat, sorghum, teff, and quinoa flours can produce dough and gluten-free bread with high sensory quality. When compound sourdough and bread were compared with native wheat dough and bread (control), the sourdough-containing bread had higher sensory quality [It is possible that the use of dried yeast with strength . It was of bread . The ferof bread . Concernutilized . It has tive SCB . Moreove quality .Germination of sorghum grains before milling, followed by fermentation by LAB, can increase the proportion of nutrients and improve the digestion of protein and starch. This process can also significantly reduce the proportion of anti-nutrients in SF, which can interfere with the absorption of nutrients . FurtherIn general, the technical characteristics of SFs do not meet the manufacturing requirements well based on factors such as rheology, pasting, X-ray differentiation, and morphology characteristics. However, modifications and additions to SFs can alter their technical characteristics and functions, making them excellent for use in the bakery and other industries. SB and SCB have become of interest to researchers due to their ability to meet the requirements of celiac disease. Moreover, they allow for optimal utilization of sorghum, which is one of the most important cereal crops for many African countries. Sorghum is characterized by its high content of natural antioxidants, minerals, and dietary fiber; however, it also contains anti-nutritional factors. Upon reviewing the literature, it was concluded that producing sorghum bread with satisfactory quality is challenging due to the nature of SF. Therefore, various additions or improvements to flour have been explored, such as adding hydrocolloids, merging with legume powders or some and other grains flour, or treating the flour through fermentation, thermal moisture treatment, extrusion cooking, dry heat treatment, and microwave processing. Adding hydrocolloids to SF alters the dough’s rheology, affecting the properties of bread and other products. The mechanism behind hydrocolloid action involves modifying the dough’s viscoelastic behavior and extensional properties, resulting in improved bread texture quality and extended shelf life. As for the heat-moisture treatment, extrusion and dry heat have been proven to increase fiber content, particularly resistant starch, which is vital for nutrition. Moreover, fermentation improves the flavor and texture of the products. In summary, it can be concluded that utilizing different treatment techniques for SF is essential for achieving technical, functional, and nutritional purposes objectives. In conclusion, in addition to bread, it can be recommended to use processed and unprocessed SF to enhance cakes, biscuits, and school breakfast meals to add nutritional value to them.