The fermentation of Malaysian fish sauce (budu) varies from one to twelve months depending on the producer, resulting in inconsistent quality. The microbiota, their predicted metabolic pathways and volatile metabolites profiles were determined at different stages of budu fermentation. Budu fermented for 1 and 3 months were characterized by the presence of Gram negative Enterobacterales, Gammaproteobacteria, and Fusobacteriaceae, which continuously decrease in abundance over fermentation time. The metabolic pathways prediction grouped 1- and 3- month budu in a cluster enriched with degradation reactions. 6-month budu were dominated by Halanaerobium and Staphylococcus, while the 12-month were dominated by Lentibacillus, Bacilli, and Halomonas. Biosynthesis-type predicted pathways involving protein and lipid derivatives were enriched in 6- and 12-month fermented budu, accumulating 2,6-dimethylpyrazine, methyl 2-ethyldecanoate, 2-phenylacetaldehyde, 3-methylbutanal, and 3-methylbutanoic acid. These compounds may indicate budu maturity and quality. This result may assist as a reference for quality control and fermentation monitoring.
Bacillus velezensis FS26 is a bacterium from the genus Bacillus that has been proven as a potential probiotic in aquaculture with a good antagonistic effect on Aeromonas spp. and Vibrio spp. Whole-genome sequencing (WGS) allows a comprehensive and in-depth analysis at the molecular level, and it is becoming an increasingly significant technique in aquaculture research. Although numerous probiotic genomes have been sequenced and investigated recently, there are minimal data on in silico analysis of B. velezensis as a probiotic bacterium isolated from aquaculture sources. Thus, this study aims to analyse the general genome characteristics and probiotic markers from the B. velezensis FS26 genome with secondary metabolites predicted against aquaculture pathogens. The B. velezensis FS26 genome (GenBank Accession: JAOPEO000000000) assembly proved to be of high quality, with eight contigs containing 3,926,371 bp and an average G + C content of 46.5%. According to antiSMASH analysis, five clusters of secondary metabolites from the B. velezensis FS26 genome showed 100% similarity. These clusters include Cluster 2 (bacilysin), Cluster 6 (bacillibactin), Cluster 7 (fengycin), Cluster 8 (bacillaene), and Cluster 9 (macrolactin H), which signify promising antibacterial, antifungal, and anticyanobacterial agents against pathogens in aquaculture. The probiotic markers of B. velezensis FS26 genome for adhesion capability in the hosts' intestine, as well as the acid and bile salt-tolerant genes, were also detected through the Prokaryotic Genome Annotation System (Prokka) annotation pipeline. These results are in agreement with our previous in vitro data, suggesting that the in silico investigation facilitates establishing B. velezensis FS26 as a beneficial probiotic for use in aquaculture.
The growth performance of red claw crayfish, Cherax quadricarinatus, fed diets with different sources and concentrations of natural calcium was evaluated. Formulated diets containing 30% protein and 8% lipid were prepared using supplementation of 0 (control), 3%, 6%, 9% eggshell, and 6% seashell. C. quadricarinatus juveniles with an average total weight of 0.21 ± 0.01 g and length of 25.0 ± 0.10 mm were obtained from ten ovigerous females bred in captivity. An aquarium with a size of 0.72 m² was divided into eight compartments with an area of 0.09 m² per compartment and was individually stocked with juvenile crayfish. A total of eight juvenile crayfish were used per dietary treatment. There were five dietary treatments in total and each of these treatments were replicated three times. The addition of eggshell and seashell powder exerted positive effects on the growth performance, molting frequency, and survival of the crayfish. Crayfish fed with a 6% eggshell-supplemented diet exhibited the best overall growth performance. The calcium percentage of the carapace increased with the increase in calcium content of the diets. Meanwhile, the performance of diets comprising eggshells and seashells was not significantly different (P > 0.05). Considering the low cost and abundance of eggshells, the addition of 6% of this product to the diet is recommended for the best growth of juvenile C. quadricarinatus.
Cancer is one of the deadliest diseases, causing million of deaths each year globally. Conventional anti-cancer therapies are non-targeted and have systemic toxicities limiting their versatile applications in many cancers. So, there is an unmet need for more specific therapeutic options that will be effective as well as free from toxicities. Antibody-drug conjugates (ADCs) are suitable alternatives with the right potential and improved therapeutic index for cancer therapy. The ADCs are highly precise new class of biopharmaceutical products that covalently linked a monoclonal antibody (mAb) (binds explicitly to a tumor-associated surface antigen) with a customized cytotoxic drug (kills cancer cells) and tied via a chemical linker (releases the drug). Due to its precise design, it brings about the target cell killing sparing the normal counterpart and free from the toxicities of conventional chemotherapy. It has never been so easy to develop potential ADCs for successful therapeutic usage. With relentless efforts, it took almost a century for scientists to advance the formula and design ADCs for its current clinical applications. Until now, several ADCs have passed successfully through preclinical and clinical trials and because of proven efficacy, a few are approved by the FDA to treat various cancer types. Even though ADCs posed some shortcomings like adverse effects and resistance at various stages of development, with continuous efforts most of these limitations are addressed and overcome to improve their efficacy. In this review, the basics of ADCs, physical and chemical properties, the evolution of design, limitations, and future potentials are discussed.
Diagnosing and finding the disease in medical sciences is a complex procedure. The basic steps involved in finding starts with signs, symptoms, and test. This study is based on the diagnosis of a skin disorder. The identification of a disease has been made on the basis of symptoms that sometimes show bipolarity. To address this bipolarity, the bipolar fuzzy sets are used as bipolar fuzzy sets cover the positive as well as negative aspects of a specific symptom. It is combined with the idea of soft sets, which gives more precise results. We have proposed a new technique in which a correlation coefficient is used to measure bipolar fuzzy soft set, which has been applied for diagnosis. The BFSSs deal most effectively with dual and fuzzy information. The correlation coefficient and the weighted correlation coefficient of BFSSs are suggested in this research. Based on said techniques, the decision-making method is suggested under a bipolar fuzzy environment to resolve ambiguous and unclear information. The implementation and effectiveness of the proposed and existing strategy has been checked by numerical computation.
Modeling three-dimensional contaminant transport released from arbitrary shape source geometries is useful in hydrological and environmental sciences. This article produces several analytical solutions for three-dimensional contaminant transport in a homogeneous and isotropic aquifer by using Green's function with the groundwater flow which is assumed to be in three directions. The solutions are obtained for both finite depth aquifer and semi-infinite depth aquifer. Various types of sources are discussed: point, line, plane, or cuboid sources. The continuous and instantaneous sources are also investigated. A MATLAB coding is developed to calculate the numerical integrals which occur at the solutions. Some solutions are verified with the solutions obtained in the literature. This study confirms the effect of groundwater velocities in all directions on the degree and the directions of contaminant spreading. Additionally, the results highlight the significant effect of the geometrical shape of the contaminant sources on contaminant concentrations for instantaneous and continuous sources. In particular, the cuboid source and the horizontal rectangular source provide the highest concentrations. The analytical solutions developed in this article can be applied for a wide range of contaminant transport.
There is no consensus regarding the classification of optic neuritis, and precise diagnostic criteria are not available. This reality means that the diagnosis of disorders that have optic neuritis as the first manifestation can be challenging. Accurate diagnosis of optic neuritis at presentation can facilitate the timely treatment of individuals with multiple sclerosis, neuromyelitis optica spectrum disorder, or myelin oligodendrocyte glycoprotein antibody-associated disease. Epidemiological data show that, cumulatively, optic neuritis is most frequently caused by many conditions other than multiple sclerosis. Worldwide, the cause and management of optic neuritis varies with geographical location, treatment availability, and ethnic background. We have developed diagnostic criteria for optic neuritis and a classification of optic neuritis subgroups. Our diagnostic criteria are based on clinical features that permit a diagnosis of possible optic neuritis; further paraclinical tests, utilising brain, orbital, and retinal imaging, together with antibody and other protein biomarker data, can lead to a diagnosis of definite optic neuritis. Paraclinical tests can also be applied retrospectively on stored samples and historical brain or retinal scans, which will be useful for future validation studies. Our criteria have the potential to reduce the risk of misdiagnosis, provide information on optic neuritis disease course that can guide future treatment trial design, and enable physicians to judge the likelihood of a need for long-term pharmacological management, which might differ according to optic neuritis subgroups.
Pathogens from the Vibrio and Aeromonas genera often cause detrimental effects to the aquaculture sector. Previously, antibiotics was used to resolve the infections, but this caused the spread of antibiotic resistant bacteria and antibiotic resistance genes into the environment. As an approach to address this issue, probiotic bacteria were introduced to improve the hosts' microbiome, disease protection, health condition, growth efficiency, feed consumption, stress response and general vigour. However, reports showed that some commercially available probiotics were restricted to a small number of microbial species and there are inconsistencies concerning its effectiveness. Hence, the aim of this study was to isolate and evaluate new Bacillus spp. from the gut of giant freshwater prawn as potential probiotics. Three Bacillus spp. isolates, Bacillus subtilis FS6 (MZ960135), Bacillus velezensis FS26 (MZ960133) and Bacillus pumilus FS97 (MZ960136) were characterised, and in vitro testing showed good probiotic properties which can help in dealing with diseases in aquaculture. Among the Bacillus spp., Bacillus velezensis FS26 showed higher antimicrobial activity towards Aeromonas hydrophila LMG 13658 and Aeromonas veronii clone DK-A. veronii-27 at 23.7 mm and 25 mm, respectively. Bacillus subtilis FS6 and Bacillus velezensis FS26 resulted in good adherence to both xylene and chloroform hydrocarbons. The Bacillus spp. isolated displayed high survivability towards 0.3% bile salt and exhibited amylase, protease, and lipase activities. Thus, the isolated Bacillus spp. are considered safe based on the sensitivity analysis towards antibiotics and γ-haemolytic activity.
This study was conducted to evaluate public awareness about COVID with aimed to check public strategies against COVID-19. A semi structured questionnaire was collected and the data was analyzed using some statistical tools (PLS-SEM) and artificial neural networks (ANN). We started by looking at the known causal linkages between the different variables to see if they matched up with the hypotheses that had been proposed. Next, for this reason, we ran a 5,000-sample bootstrapping test to assess how strongly our findings corroborated the null hypothesis. PLS-SEM direct path analysis revealed HRP -> PA-COVID, HI -> PA-COVID, MU -> PA-COVID, PM -> PA-COVID, SD -> PA-COVID. These findings provide credence to the acceptance of hypotheses H1, H3, and H5, but reject hypothesis H2. We have also examined control factors such as respondents' age, gender, and level of education. Age was found to have a positive correlation with PA-COVID, while mean gender and education level were found to not correlate at all with PA-COVID. However, age can be a useful control variable, as a more seasoned individual is likely to have a better understanding of COVID and its effects on independent variables. Study results revealed a small moderation effect in the relationships between understudy independent and dependent variables. Education significantly moderates the relationship of PA-COVID associated with MU, PH, SD, RP, PM, PA-COVID, depicts the moderation role of education on the relationship between MU*Education->PA-COVID, HI*Education->PA.COVID, SD*Education->PA.COVID, HRP*Education->PA.COVID, PM*Education -> PA.COVID. The artificial neural network (ANN) model we've developed for spreading information about COVID-19 (PA-COVID) follows in the footsteps of previous studies. The root means the square of the errors (RMSE). Validity measures how well a model can predict a certain result. With RMSE values of 0.424 for training and 0.394 for testing, we observed that our ANN model for public awareness of COVID-19 (PA-COVID) had a strong predictive ability. Based on the sensitivity analysis results, we determined that PA. COVID had the highest relative normalized relevance for our sample (100%). These factors were then followed by MU (54.6%), HI (11.1%), SD (100.0%), HRP (28.5%), and PM (64.6%) were likewise shown to be the least important factors for consumers in developing countries struggling with diseases caused by contaminated water. In addition, a specific approach was used to construct a goodness-of-fit coefficient to evaluate the performance of the ANN models. The study will aid in the implementation of effective monitoring and public policies to promote the health of local people.
Malignant melanoma is considered one of the deadliest skin diseases if ignored without treatment. The mortality rate caused by melanoma is more than two times that of other skin malignancy diseases. These facts encourage computer scientists to find automated methods to discover skin cancers. Nowadays, the analysis of skin images is widely used by assistant physicians to discover the first stage of the disease automatically. One of the challenges the computer science researchers faced when developing such a system is the un-clarity of the existing images, such as noise like shadows, low contrast, hairs, and specular reflections, which complicates detecting the skin lesions in that images. This paper proposes the solution to the problem mentioned earlier using the active contour method. Still, seed selection in the dynamic contour method has the main drawback of where it should start the segmentation process. This paper uses Gaussian filter-based maximum entropy and morphological processing methods to find automatic seed points for active contour. By incorporating this, it can segment the lesion from dermoscopic images automatically. Our proposed methodology tested quantitative and qualitative measures on standard dataset dermis and used to test the proposed method's reliability which shows encouraging results.
During the COVID-19 pandemic, online teaching modes were found vital to continue students' learning process, but sustainable implementation of online teaching models is an area of concern for policymakers. Psychiatrists are also eager to know students' behavior toward learning and modes of teaching during COVID-19. We have drawn a model based on the big five personality traits to study students' satisfaction with online teaching modes and their adoption intentions toward online teaching modes. We have collected data from 718 bachelor's and master's level students from four different universities. We have applied the SEM-ANN dual-stage approach to test personality traits' influence and ranked them based on their normalized importance. The results revealed that agreeableness, conscientiousness, neuroticism, and openness positively influence students' satisfaction with online teaching models, but that extraversion negatively influences their satisfaction. Agreeableness, extraversion, and neuroticism positively impact, but openness negatively influences. Conscientiousness does not affect adoption intention. Furthermore, agreeableness is the most significant, and conscientiousness is the least important factor for students to adopt online teaching modes. The findings of the study have useful perceptiveness for educational policymakers, academics, and psychiatrists.
Understanding the pharmacokinetics parameter of colistin methanesulfonate sodium (CMS) and colistin is needed to optimize the dosage regimen in critically ill patients. However, there is a scarcity of pharmacokinetics parameters in this population. This review provides a comprehensive understanding of CMS and colistin pharmacokinetics parameters in this population. The relevant studies published in English that reported on the pharmacokinetics of CMS and colistin from 2000 until 2020 were systematically searched using the PubMed and Scopus electronic databases. Reference lists of articles were reviewed to identify additional studies. A total of 252 citation titles were identified, of which 101 potentially relevant abstracts were screened, and 25 full-text articles were selected for detailed analysis. Of those, 15 studies were included for the review. This review has demonstrated vast inter-study discrepancies in colistin plasma concentration and the pharmacokinetics parameter estimates. The discrepancies might be due to complex pathophysiological changes in the population studied, differences in CMS brand used, methodology, and study protocol. Application of loading dose of CMS and an additional dose of CMS after dialysis session was recommended by some studies. In view of inter-patient and intra-patient variability in colistin plasma concentration and pharmacokinetics parameters, personalized colistin dosing for this population is recommended.
The objectives of this study were to investigate the prevalence and associated risk factors for gastrointestinal (GI) parasites in buffaloes from various areas of Sarawak, and to assess current management practices of GI parasites among farmers. Faecal samples were collected from 15 farms and 129 animals, as well as data on farm and animal-based characteristics. A total of 129 faecal samples were examined for GI parasites using a modified McMaster and sedimentation. Association between potential risk factors and the prevalence of GI parasites was investigated using Chi-square statistic. The prevalence of Paramphistomum sp., strongyles, and coccidia were 75.2% (95% CI±7.5), 52.7% (95% CI±8.6) and 48.1% (95% CI±8.6), respectively. Farms which had a grazing area less than 50 acres in size had significantly higher prevalence of strongyles (70.5%, χ2 = 8.34, P = 0.004) and paramphistomes (88.6%, χ2 = 6.46, P = 0.01) relative to farms with a larger grazing area (43.5% and 68.2%, respectively). Prevalence of strongyles was lower in farms that did not implement a cut- and-carry system (45.6%, χ2 = 4.17, P = 0.04) in comparison to those that did (64%). The prevalence of paramphistomes was higher on farms with more than 40 animals (80.6%, χ2 = 3.18, P = 0.05) relative to farms with fewer animals. The majority of farmers surveyed (67.9%) showed awareness of GI parasite infection and reported that they recognized the associated symptoms. Most farmers practised deworming, and ivermectin was the most commonly used anthelminthic (60.4%); only 1.9% of farmers used albendazole. Overall this study revealed a high prevalence of GI parasites in buffalo in Sarawak. Although farmers report they are aware of parasitic diseases, further education is still required. This could include how they can successfully implement on-farm changes to reduce the prevalence of GI parasites in their herds.
Mass spectrometry-based proteomics relies on dedicated software for peptide and protein identification. These software include open-source or commercial-based search engines; wherein, they employ different algorithms to establish their scoring and identified proteins. Although previous comparative studies have differentiated the proteomics results from different software, there are still yet studies specifically been conducted to compare and evaluate the search engine in the field of halal analysis. This is important because the halal analysis is often using commercial meat samples that have been subjected to various processing, further complicating its analysis. Thus, this study aimed to assess three open-source search engines (Comet, X! Tandem, and ProteinProspector) and a commercial-based search engine (ProteinPilot™) against 135 raw tandem mass spectrometry data files from 15 types of pork-based food products for halal analysis. Each database search engine contained high false-discovery rate (FDR); however, a post-searching algorithm called PeptideProphet managed to reduce the FDR, except for ProteinProspector and ProteinPilot™. From this study, the combined database search engine (executed by iProphet) reveals a thorough protein list for pork-based food products; wherein the most abundant proteins are myofibrillar proteins. Thus, this proteomics study will aid the identification of potential peptide and protein biomarkers for future precision halal analysis. SIGNIFICANCE: A critical challenge of halal proteomics is the availability of a database to confirm the inferential peptides as well as proteins. Currently, the established database such as UniProtKB is related to animal proteome; however, the halal proteomics is related to the highly processed meat-based food products. This study highlights the use of different database search engines (Comet, X! Tandem, ProteinProspector, and ProteinPilot™) and their respective algorithms to analyse 135 raw tandem mass spectrometry data files from 15 types of pork-based food products. This is the first attempt that has compared different database search engines in the context of halal proteomics to ensure the effectiveness of controlling the FDR. Previous studies were just focused on the advantages of a certain algorithm over another. Moreover, other previous studies also have mainly reported the use of mass spectrometry-based shotgun proteomics for meat authentication (the most similar field to halal analysis), but none of the studies were reported on halal aspects that used samples originated from highly processed food products. Hence, a systematic comparative study is duly needed for a more comprehensive and thorough proteomics analysis for such samples. In this study, our combinatorial approach for halal proteomics results from the different search engines used (Comet, X! Tandem, and ProteinProspector) has successfully generated a comprehensive spectral library for the pork-based meat products. This combined spectral library is freely available at https://data.mendeley.com/datasets/6dmm8659rm/3. Thus far, this is the first and new attempt at establishing a spectral library for halal proteomics. We also believe this study is a pioneer for halal proteomics that aimed at non-conventional and non-model organism proteomics, protein analytics, protein bioinformatics, and potential biomarker discovery.
Determination of a microbial strain for the joining into sustenance items requires both in vitro and in vivo assessment. A newly isolated bacteriocin-like inhibitory substance (BLIS) producing lactic acid bacterium, Lactococcus lactis Gh1, was isolated from a traditional flavour enhancer and evaluated in vitro for its potential applications in the food industry. Results from this study showed that L. lactis was tolerant to NaCl (≤ 4.0%, w/v), phenol (≤ 0.4%, w/v), 0.3% (w/v) bile salt, and pH 3. BLIS from L. lactis showed antimicrobial activity against Listeria monocytogenes ATCC 15313 and was susceptible to 10 types of antibiotics. The absence of haemolytic activity and the presence of acid phosphatase and naphthol-AS-BI-phosphohydrolase were observed in L. lactis. L. lactis could coagulate milk and showed a negative response to amylolytic and proteolytic activities and did not secrete β-galactosidase. The antimicrobial activity of BLIS was completely abolished at 121 °C. The BLIS was conserved at 4 °C in BHI and MRS medium up to 6-4 months, respectively. BLIS activity was more stable in BHI as compared to MRS after four freeze-thaw cycles and was not affected by a wide range of pH (pH 4-8). BLIS was sensitive to proteinase k and resistant to catalase and trypsin. The antimicrobial activity was slightly reduced by acetone, ethanol, methanol, and acetonitrile at 10% (v/v) and also towards Tween-80, urea, and NaCl 1% (v/v). Results from this study have demonstrated that L. lactis has a vast potential to be applied in the food industry, such as for the preparation of starter culture, functional foods, and probiotic products.
Bacteriocin-like inhibitory substances (BLIS) produced by Lactococcus lactis Gh1 had shown antimicrobial activity against Listeria monocytogenes ATCC 15313. Brain Heart Infusion (BHI) broth is used for the cultivation and enumeration of lactic acid bacteria, but there is a need to improve the current medium composition for enhancement of BLIS production, and one of the approaches is to model the optimization process and identify the most appropriate medium formulation. Response surface methodology (RSM) and artificial neural network (ANN) models were employed in this study. In medium optimization, ANN (R2 = 0.98) methodology provided better estimation point and data fitting as compared to RSM (R2 = 0.79). In ANN, the optimal medium consisted of 35.38 g/L soytone, 16 g/L fructose, 3.25 g/L sodium chloride (NaCl) and 5.40 g/L disodium phosphate (Na2HPO4). BLIS production in optimal medium (717.13 ± 0.76 AU/mL) was about 1.40-fold higher than that obtained in nonoptimised (520.56 ± 3.37 AU/mL) medium. BLIS production was further improved by about 1.18 times higher in 2 L stirred tank bioreactor (787.40 ± 1.30 AU/mL) as compared to that obtained in 250 mL shake flask (665.28 ± 14.22 AU/mL) using the optimised medium.
Gelatin and collagen are considered halal-critical ingredients as they are typically derived from either bovine or porcine animals. Current analytical methods for determining the sources of gelatin and collagen suffer from limitations in terms of robustness and false positives in peptide matching. Thus, the aim of this study was to investigate the utility of monitoring hydroxyproline, a signature amino acid for gelatin and collagen, for identifying potentially haram foodstuffs. To determine the hydroxyproline profiles among animal- and plant-based samples, one-way univariate analysis of variance followed by pair-wise comparison was used to establish statistical significance. Multivariate chemometric analysis through principal component analysis revealed a discrete distribution pattern among 59 samples due to hydroxyproline variability. Finally, inter- and intra-laboratory comparisons demonstrated the validity and robustness of hydroxyproline determination according to ISO 17025. Thus, this preliminary identification technique will aid the identification of potentially haram foodstuffs.
This study aims to examine the association of orofacial pain and oral health status and oral health behaviours in facial burn patients. The participants in this cross-sectional study were randomly recruited from the Burn Care Center, Institute of Medical Sciences, Islamabad, Pakistan. An intraoral evaluation was carried out to record the DMFT and OHI-S. A self-administered questionnaire was used to collect information on sociodemographic status, brushing frequency, and dental visits. Orofacial pain during mandibular movement was assessed using the Visual Analogue Scale (VAS). Psychological status was assessed using the Generalized Anxiety Disorder Scale and Impact of Events Scale. ANOVA and simple and multiple linear regression tests were used to analyse the data. From the 90 facial burn patients included, the majority were below 34 years of age, female, single or divorced, and unemployed. The mean DMFT was 10.7, and 71% had poor oral hygiene. 56% of the participants had moderate-to-severe anxiety, and 68% had posttraumatic stress disorder. 53% of the participants had moderate-to-severe pain during mouth opening or moving the mandible with a mean score of 41.5. Analyses showed that orofacial pain was associated with less frequent brushing, irregular dental visits, greater DMFT score, and more plaque accumulation (OHI-S). It was also associated with employment status, the severity of a burn, anxiety, and stress. The treatment and management of dental and oral conditions in burn patients need judicious balance in controlling and accurate assessment of the pain and improving psychological problems in burn patients.
The emergence of antibiotic-resistant bacteria has become a significant and ever-increasing threat to global public health, increasing both morbidity and mortality rates, and the financial burden on health services. Infection by drug-resistant bacteria is anticipated to contribute to the demise of almost 10 million people by the year 2050 unless a competent and effective response is devised to engage with this issue. The emergence and spread of resistance are commonly caused by the excessive or inappropriate use of antibiotics and substandard pharmaceuticals. It arises when pathogens adapt to different conditions and develop self-defence mechanisms. Currently, novel antimicrobial peptides (AMPs) have been reported to be the sole cure for some clinical cases of infectious diseases such as sepsis and skin infections, although these agents may, on occasion, require administration together with an adjunctive low-dose antibiotic. Although AMPs are a promising alternative form of anti-microbial therapy and easily applied in the medical sector, they still have limitations that should not be taken lightly. Hence, this review explores the characteristics, advantages and disadvantages of AMPs for their potential in treating antibiotic-resistant pathogens.