Background and Objectives: Besides classical stapedotomy, reverse stapedotomy has been used for many years in the management of otosclerosis. Our study aims to investigate whether reversing the surgical steps in stapedotomy impacts vestibular function and hearing improvement. Materials and Methods: A cohort of 123 patients underwent either classic or reverse stapedotomy procedures utilizing a fiber–optic argon laser. Audiological assessments, following the guidelines of the Committee on Hearing and Equilibrium, were conducted, including pure tone average, air–bone (AB) gap, overclosure, and AB gap closure. Vestibular evaluation involved pre- and postoperative comparison of rotatory test parameters, including frequency, amplitude, and slow phase velocity of nystagmus. Results: The study demonstrated an overall median overclosure of 3.3 (3.3, 5.0) dB and a mean AB gap closure of 20.3 ± 8.8 dB. Postoperative median AB gap was 7.5 (7.5, 11.3) dB in the reverse stapedotomy group and 10.0 (10.0, 12.5) dB in the classic stapedotomy group. While overclosure and AB gap closure were marginally superior in the reverse stapedotomy group, these differences did not reach statistical significance. No significant disparities were observed in the frequency, slow phase velocity, or amplitude of nystagmus in the rotational test. Conclusions: Although not always possible, reverse stapedotomy proved to be a safe surgical technique regarding postoperative outcomes. Its adoption may mitigate risks associated with floating footplate, sensorineural hearing loss, and incus luxation/subluxation, while facilitating the learning curve for less experienced ear surgeons. Full article

The chalkiness, starch fine structure, and physiochemical properties of rice starch were analyzed and their correlations were investigated under different nighttime temperatures during the early grain-filling stage. Compared to MT, medium temperature (MT) and low (LNT) and high (HNT) nighttime temperatures resulted in an increased chalky grain rate (CGR) and chalkiness degree (CD). LNT mainly affected the chalkiness by increasing peak1 (short branch chains of amylopectin), the branching degree, and the proportion of small starch granules but decreasing peak2 (long branch chains of amylopectin) and peak3 (amylose branches). This altered the pasting properties, such as by increasing the peak viscosity and final viscosity. However, HNT mainly affected the chalkiness by increasing peak2 and the crystallinity degree but decreasing peak1 and peak3. Regarding the thermal properties, HNT also elevated peak and conclusion temperatures. The CGR and CD were significantly and positively correlated with the proportions of small and medium starch granules, peak1, branching degree, gelatinization enthalpy, setback viscosity, and pasting time but markedly and negatively correlated with the proportion of large starch granules, amylose content, peak3, peak viscosity, and breakdown viscosity. These findings suggest that LNT and HNT disrupted the starch structure, resulting in increased chalkiness. However, their mechanisms of action differ. Full article

The challenge of denoising low-dose computed tomography (CT) has garnered significant research interest due to the detrimental impact of noise on CT image quality, impeding diagnostic accuracy and image-guided therapies. This paper introduces an innovative approach termed the Wavelet Domain Dual Forward Denoising Stream Network (WaveletDFDS-Net) to address this challenge. This method ingeniously combines convolutional neural networks and Transformers to leverage their complementary capabilities in feature extraction. Additionally, it employs a wavelet transform for efficient image downsampling, thereby preserving critical information while reducing computational requirements. Moreover, we have formulated a distinctive dual-domain compound loss function that significantly enhances the restoration of intricate details. The performance of WaveletDFDS-Net is assessed by comparative experiments conducted on public CT datasets, and results demonstrate its enhanced denoising effect with an SSIM of 0.9269, PSNR of 38.1343 and RMSE of 0.0130, superior to existing methods. Full article

Change-point detection is a challenging problem that has a number of applications across various real-world domains. The primary objective of CPD is to identify specific time points where the underlying system undergoes transitions between different states, each characterized by its distinct data distribution. Precise identification of change points in time series omics data can provide insights into the dynamic and temporal characteristics inherent to complex biological systems. Many change-point detection methods have traditionally focused on the direct estimation of data distributions. However, these approaches become unrealistic in high-dimensional data analysis. Density ratio methods have emerged as promising approaches for change-point detection since estimating density ratios is easier than directly estimating individual densities. Nevertheless, the divergence measures used in these methods may suffer from numerical instability during computation. Additionally, the most popular $\alpha$-relative Pearson divergence cannot measure the dissimilarity between two distributions of data but a mixture of distributions. To overcome the limitations of existing density ratio-based methods, we propose a novel approach called the Pearson-like scaled-Bregman divergence-based (PLsBD) density ratio estimation method for change-point detection. Our theoretical studies derive an analytical expression for the Pearson-like scaled Bregman divergence using a mixture measure. We integrate the PLsBD with a kernel regression model and apply a random sampling strategy to identify change points in both synthetic data and real-world high-dimensional genomics data of Drosophila. Our PLsBD method demonstrates superior performance compared to many other change-point detection methods. Full article

Seismic reflection data and implicitly sonic velocity are undoubtedly the most important source of information for large-scale subsurface characterization. Yet, deriving reservoir and fluid flow properties from acoustic data is still challenging in carbonates, which display large acoustic velocity variations that contest many of the conventional assumptions regarding wave propagation in porous media. In this comprehensive study on 370 carbonate samples (247 limestones and 123 dolomites), we re-evaluate the impact of mineral velocity on bulk rock acoustic properties of dolomite and limestone by assessing the link between sonic velocity and the rock’s pore geometry. We quantify pore size and pore network complexity using parameters from both digital image analysis (DIA) and the extended Biot theory (EBT). We then compare DIA and EBT parameters to assess the impact of pore network geometry versus mineral velocity on the acoustic velocity of carbonate rocks. We explore the usefulness of EBT parameter γ_k in improving permeability estimates. Published values of velocity indicate that dolomites exhibit higher velocities than limestones at any given porosity. Our laboratory measurements of acoustic velocity, however, reveal that both dolomites and limestones show extreme variations in sonic velocities where samples with compressional velocity of ~5000 m/s may range in porosity from 5% to 25% and samples with porosity of ~20% may range in velocity from ~4000 m/s to 5700 m/s. Through the quantitative assessment of the pore network in our samples we document that pore network geometry has much more impact on the acoustic velocity of carbonates than variations in mineralogy, in this case dolomite and calcite. Most of the dolostone samples studied are dominated by small pores, resulting in relatively low velocities for their given porosity, while limestones with similar velocity–porosity values often possess simpler pore networks with larger pores. This pore size difference offsets the faster velocity of dolomite. The extended Biot theory parameter γ_k, captures this variation in pore size and internal geometry and exhibits a strong correlation to specific surface. Moreover, γ_k captures the impact of internal pore geometry on acoustic velocity, providing the basis for challenging existing assumptions regarding the importance of mineral velocity. By quantifying internal geometry, γ_k can improve permeability estimates in reservoir characterization and enhance evaluations of producibility and injectability. With that, it has direct implications on general geophysics, hydrocarbon exploration, and CCS initiatives. Full article

This study addresses the co-pyrogasification of municipal solid waste (MSW) from the Environmental Technology Park, San Juan, Argentina. This process involves heating waste at high temperatures in a low-oxygen or oxygen-free atmosphere as a sustainable strategy for waste management and energy generation. The principal objective is to focus on understanding the MSW co-pyrogasification kinetics to enhance performance in reactor design. A representative sample of MSW collected over a month was analyzed, focusing on the variation in mass proportions of plastic, organic matter, and paper. The empirical methodology included the deconvolution of macro-TGA curves and deep learning algorithms to predict and validate macro-TG data during co-pyrogasification. The findings reveal that MSW is a solid matrix more easily treated on thermochemical platforms, with kinetic and thermodynamic parameters favoring its processing. This approach suggests that MSW co-pyrogasification may represent a feasible alternative for resource recovery and bioenergy production, supporting the policies for the transition to a cleaner future and a circular economy. Full article

The well-known deletion of coda sibilants in Old French (11th–14th centuries) induced a compensatory lengthening effect on the preceding vowel, generally described as applying uniformly where coda /s/ was lost. This study highlights and analyzes phonological contexts where lengthening likely did not occur, examining their interaction with stress assignment, vowel quality, schwa adjustment, prothesis, and morphological structure. The Stratal OT analysis formalizes the proposed pattern differentiating the long and short vowel reflexes identified especially for mid vowels: while categorical in tonic syllables and low vowels /a, ɑ/ irrespective of stress, lengthening only prevails in atonic mid vowels when coda /s/ deletion impacts a syllable assigned stress within the specific stratal phonological cycle when /s/ is deleted from input. The resulting length is transmitted and preserved in subsequent stratal cycles regardless of eventual word-level stress reassignment, especially (but not exclusively) because of word-level schwa adjustment, allowing a shift to word-final stress and producing an opacity effect of a long atonic mid vowel inherited from an earlier cycle. The stratal account formalizes observed analogical effects between lexical items and derived forms with respect to vowel quality and length and proposes them to result instead from the interplay of morphology and phonology. Full article

Background: Sarcopenic obesity (SO) is the combination of excess fat, skeletal muscle and muscular strength/function deficit. The ESPEN/EASO have proposed new diagnostic criteria, but the SO prevalence in patients with severe obesity remains to be established. The aim of this study was to establish the SO prevalence in a large cohort of inpatients with obesity, considering sex, age, BMI, type, and number of concomitant diseases. Methods: Patient data of both genders aged between 18 and 90 years with a body mass index (BMI) of ≥30 kg/m² underwent hospital evaluation including bioelectrical impedance analysis (BIA) and handgrip strength (HS). QoL scores were obtained by the Psychological General Well-Being Index questionnaire. The study was approved by the institutional Ethic Committee. Results: Among the 3858 patients, 444 (11.51%) exhibited a strength deficit, while 3847 (99.71%) had skeletal muscle mass deficit. The prevalence of SO was then 11.48%, with higher rates in women (12.39%), in individuals aged >70 years (27%), and in those reporting a ‘poor’ QoL (12.6%). No significant difference in SO prevalence was found when stratifying by BMI (30–40 kg/m² vs. >40 kg/m², p = 0.1710). In SO patients, osteoarticular diseases (57%), hypertension/heart failure (38%), type 2 diabetes mellitus (34%), and obstructive sleep apnea (32%) were the more frequent comorbidities. Conclusions: The application of ESPEN/EASO-SO criteria in a cohort of inpatients with severe obesity revealed 11.48% SO prevalence, which was associated with age (particularly > 70 years), gender (women), but not BMI, as determinants. Disease staging and QoL screening may improve the identification of SO high-risk patients. Full article

Sound and heat insulation are among the most important concerns in modern life and nonwoven composite structures are highly effective in noise reduction and heat insulation. In this study, three layered nonwoven composite structures composed of a recycled polyester (r-Pet)-based thermo-bonded nonwoven outer layer and meltblown nonwovens from Polypropylene (PP) and Polybutylene terephthalate (PBT) as inner layers were formed to provide heat and sound insulation. Fiber fineness and cross-section of the thermo-bonded outer layer, fiber type (PP/PBT), areal weight (100/200 g/m²) and process conditions (calendared/non-calendared) of the meltblown inner layer were changed systematically and the influence of these independent variables on thickness, bulk density, air permeability, sound absorption coefficient and thermal resistance of composite structures were analyzed statistically by using Design Expert 13 software. Additionally, the results were compared with composite structures including an electrospun nanofiber web inner layer and with structures without an inner layer. It was concluded that comparable or even better sound absorption values were achieved with the developed nonwoven composites containing meltblown layers compared to nanofiber-included composites and the materials in previous studies. Full article

The shift towards sustainable transportation is an urgent worldwide issue, leading to the investigation of creative methods to decrease the environmental effects of traditional vehicles. Electric vehicles (EVs) are a promising alternative, but the issue lies in establishing efficient and environmentally friendly charging infrastructure. This review explores the existing research on the subject of photovoltaic-powered electric vehicle charging stations (EVCSs). Our analysis highlights the potential for economic growth and the creation of robust and decentralized energy systems by increasing the number of EVCSs. This review summarizes the current knowledge in this field and highlights the key factors driving efforts to expand the use of PV-powered EVCSs. The findings indicate that MATLAB was predominantly used for theoretical studies, with projects focusing on shading parking lots. The energy usage varied from 0.139 to 0.295 kWh/km, while the cost of energy ranged from USD 0.0032 to 0.5645 per kWh for an on-grid system. The payback period (PBP) values are suitable for this application. The average PBP was demonstrated to range from 1 to 15 years. The findings from this assessment can guide policymakers, researchers, and industry stakeholders in shaping future advancements toward a cleaner and more sustainable transportation system. Full article

The aim of this work is to obtain novel and interesting results for mild solutions to a semilinear differential inclusion involving a w-weighted, $\Phi$-Hilfer, fractional derivative of order $\mu \in (1,2)$ with non-instantaneous impulses in Banach spaces with infinite dimensions when the linear term is the infinitesimal generator of a strongly continuous cosine family and the nonlinear term is a multi-valued function. First, we determine the formula of the mild solution function for the considered semilinear differential inclusion. Then, we give sufficient conditions to ensure that the mild solution set is not empty or compact. The desired results are achieved by using the properties of both the w-weighted $\Phi$-Laplace transform, w-weighted $\psi$-convolution and the measure of non-compactness. Since the operator, the w-weighted $\Phi$-Hilfer, includes well-known types of fractional differential operators, our results generalize several recent results in the literature. Moreover, our results are novel because no one has previously studied these types of semilinear differential inclusions. Finally, we give an illustrative example that supports our theoretical results. Full article

Marine shales from the Niutitang Formation and marine–continental transitional shales from the Longtan Formation are two sets of extremely important hydrocarbon source rocks in South China. In order to quantitatively compare the pore complexity characteristics between marine and marine–continental transitional shales, the shale and kerogen of the Niutitang Formation and the Longtan Formation are taken as our research subjects. Based on organic petrology, geochemistry, and low-temperature gas adsorption analyses, the fractal dimension of their pores is calculated by the Frenkel–Halsey–Hill (FHH) and Sierpinski models, and the influences of total organic carbon (TOC), vitrinite reflectance (R_o), and mineral composition on the pore fractals of the shale and kerogen are discussed. Our results show the following: (1) Marine shale predominantly has wedge-shaped and slit pores, while marine–continental transitional shale has inkpot-shaped and slit pores. (2) Cylindrical pores are common in organic matter of both shale types, with marine shale having a greater gas storage space (CRV) from organic matter pores, while marine–continental transitional shale relies more on inorganic pores, especially interlayer clay mineral pores, for gas storage due to their large specific surface area and high adsorption capacity (CRA). (3) The fractal characteristics of marine and marine–continental transitional shale pores are influenced differently. In marine shale, TOC positively correlates with fractal dimensions, while in marine–continental shale, R_o and clay minerals have a stronger influence. R_o is the primary factor affecting organic matter pore complexity. (4) Our two pore fractal models show that the complexity of the shale in the Longtan Formation surpasses that of the shale in the Niutitang Formation, and type I kerogen has more complex organic matter pores than type III, aiding in evaluating pore connectivity and flow effectiveness in shale reservoirs. Full article

Health systems in high-resource countries recognize the importance of making decisions about the services offered to the population based on scientific evidence. Producing this evidence is especially challenging in areas such as newborn care where the frequency of conditions is rare. However, methodological advances in the field of economic evaluation could change how this evidence is used in decision-making. This study aimed to investigate how decision-makers in the Canadian province of Quebec perceive the value of recent advances in economic evaluations for perinatal studies and how these advances might affect the offer of neonatal interventions in the public health care system. A qualitative study was conducted. A total of 10 policymakers were interviewed. A neo-institutional conceptual framework highlighting three dimensions, structure, power, and interpretive schemes, was used for data collection and analyses. Structural factors, interpretative schemes, and power management between the groups concerned concur to ensure that providing services to newborns is not hindered by the difficulty of producing evidence. They also ensure that the decisions regarding which disease to screen for take into consideration the specificity of neonatology, in particular, the social value given to children not captured by available evidence. Full article

One of the significant challenges in scaling agile software development is organizing software development teams to ensure effective communication among members while equipping them with the capabilities to deliver business value independently. A formal approach to address this challenge involves modeling it as an optimization problem: given a professional staff, how can they be organized to optimize the number of communication channels, considering both intra-team and inter-team channels? In this article, we propose applying a set of bio-inspired algorithms to solve this problem. We introduce an enhancement that incorporates ensemble learning into the resolution process to achieve nearly optimal results. Ensemble learning integrates multiple machine-learning strategies with diverse characteristics to boost optimizer performance. Furthermore, the studied metaheuristics offer an excellent opportunity to explore their linear convergence, contingent on the exploration and exploitation phases. The results produce more precise definitions for team sizes, aligning with industry standards. Our approach demonstrates superior performance compared to the traditional versions of these algorithms. Full article

According to the Magnus principle, a rotating cylinder experiences a lateral force perpendicular to the incoming flow direction. This phenomenon can be harnessed to boost the lift of an airfoil by positioning a rotating cylinder at the leading edge. In this study, we simulate flapping-wing motion using the sliding mesh technique in a heaving coordinate system to investigate the energy harvesting capabilities of Magnus effect flapping wings (MEFWs) featuring a leading-edge rotating cylinder. Through analysis of the flow field vortex structure and pressure distribution, we explore how control parameters such as gap width, rotational speed ratio, and phase difference of the leading-edge rotating cylinder impact the energy harvesting characteristics of the flapping wing. The results demonstrate that MEFWs effectively mitigate the formation of leading-edge vortices during wing motion. Consequently, this enhances both lift generation and energy harvesting capability. MEFWs with smaller gap widths are less prone to induce the detachment of leading-edge vortices during motion, ensuring a higher peak lift force and an increase in the energy harvesting efficiency. Moreover, higher rotational speed ratios and phase differences, synchronized with wing motion, can prevent leading-edge vortex generation during wing motion. All three control parameters contribute to enhancing the energy harvesting capability of MEFWs within a certain range. At the examined Reynolds number, the optimal parameter values are determined to be = 0.0005, R = 3, and = 0°. Full article

The dung beetle optimization (DBO) algorithm, a swarm intelligence-based metaheuristic, is renowned for its robust optimization capability and fast convergence speed. However, it also suffers from low population diversity, susceptibility to local optima solutions, and unsatisfactory convergence speed when facing complex optimization problems. In response, this paper proposes the multi-strategy improved dung beetle optimization algorithm (MDBO). The core improvements include using Latin hypercube sampling for better population initialization and the introduction of a novel differential variation strategy, termed “Mean Differential Variation”, to enhance the algorithm’s ability to evade local optima. Moreover, a strategy combining lens imaging reverse learning and dimension-by-dimension optimization was proposed and applied to the current optimal solution. Through comprehensive performance testing on standard benchmark functions from CEC2017 and CEC2020, MDBO demonstrates superior performance in terms of optimization accuracy, stability, and convergence speed compared with other classical metaheuristic optimization algorithms. Additionally, the efficacy of MDBO in addressing complex real-world engineering problems is validated through three representative engineering application scenarios namely extension/compression spring design problems, reducer design problems, and welded beam design problems. Full article

 The valorization technique successfully transformed waste polyethylene terephthalate (PET) into valuable carbon nanomaterial (CN)/graphene, while doped and undoped ZnO nanopowders were synthesized via sol–gel methods. Utilizing XRD, BET, TEM, EDX, FTIR, and TGA analyses, the synthesis of sp² 2D sheet, pristine, and doped ZnO nanostructures was confirmed. Solid-state gas sensor devices, tested under 51% relative humidity (RH), 30 °C ambient temperature, and 0.2 flow rate, exhibited a 3.4% enhanced response to H₂ gas compared to CO₂ at 50 ppm concentrations over time. Notably, the ZnO/CN sensor surpassed CN and ZnO alone, attributed to CN dopant integration with decreasing order of response performance as ZnO/CN > CN > ZnO. This study underscores the efficacy of valorization techniques in generating high-value carbon nanomaterials and their efficacy in bolstering gas sensor performance, with ZnO/CN demonstrating superior response capabilities. Full article

The development of cell-based biomaterial alternatives holds significant promise in tissue engineering applications, but it requires accurate mechanical assessment. Herein, we present the development of a novel 3D-printed confined compression apparatus, fabricated using clear resin, designed to cater to the unique demands of biomaterial developers. Our objective was to enhance the precision of force measurements and improve sample visibility during compression testing. We compared the performance of our innovative 3D-printed confined compression setup to a conventional setup by performing stress relaxation testing on hydrogels with variable degrees of crosslinking. We assessed equilibrium force, aggregate modulus, and peak force. This study demonstrates that our revised setup can capture a larger range of force values while simultaneously improving accuracy. We were able to detect significant differences in force and aggregate modulus measurements of hydrogels with variable degrees of crosslinking using our revised setup, whereas these were indistinguishable with the convectional apparatus. Further, by incorporating a clear resin in the fabrication of the compression chamber, we improved sample visibility, thus enabling real-time monitoring and informed assessment of biomaterial behavior under compressive testing. Full article

Sesquiterpenoids served as an important source for natural product drug discovery. Although genome mining approaches have revealed numerous novel sesquiterpenoids and biosynthetic enzymes, the comprehensive landscape of fungal sesquiterpene synthases (STSs) remains elusive. In this study, 123 previously reported fungal STSs were subjected to phylogenetic analysis, resulting in the identification of a fungi-specific STS family known as trichodiene synthase-like sesquiterpene synthases (TDTSs). Subsequently, the application of hidden Markov models allowed the discovery of 517 TDTSs from our in-house fungi genome library of over 400 sequenced genomes, and these TDTSs were defined into 79 families based on a sequence similarity network. Based on the novelty of protein sequences and the completeness of their biosynthetic gene clusters, 23 TDTS genes were selected for heterologous expression in Aspergillus oryzae. In total, 10 TDTSs were active and collectively produced 12 mono- and sesquiterpenes, resulting in the identification of the first chamipinene synthase, as well as the first fungi-derived cedrene, sabinene, and camphene synthases. Additionally, with the guidance of functionally characterized TDTSs, we found that TDTSs in Family 1 could produce bridged-cyclic sesquiterpenes, while those in Family 2 could synthesize spiro- and bridged-cyclic sesquiterpenes. Our research presents a new avenue for the genome mining of fungal sesquiterpenoids. Full article

Previous studies have shown that boletes are abundant and diverse in China, especially in tropical and subtropical regions. In the present study, morphological, ecological, host relationship, and a four-locus (28S, tef1, rpb1, and rpb2) molecular phylogenetic analyses were used to study the family Boletaceae in subtropical and tropical China. Four new bluing species are described from three genera, viz. Boletellus verruculosus (Chinese name疣柄条孢牛肝菌), Xerocomellus tenuis (Chinese name细柄红绒盖牛肝菌), Xer. brunneus (Chinese name褐盖红绒盖牛肝菌), and Xerocomus zhangii (Chinese name张氏绒盖牛肝菌). Moreover, the genus Nigroboletus is treated as a synonym of Xerocomellus, and a new combination, namely Xer. roseonigrescens (Chinese name玫瑰红绒盖牛肝菌), is proposed. Full article

Autophagy, a conserved cellular recycling process, plays a crucial role in maintaining homeostasis under stress conditions. It also regulates the development and virulence of numerous filamentous fungi. In this study, we investigated the specific function of ATG8, a reliable autophagic marker, in the opportunistic pathogen Aspergillus flavus. To investigate the role of atg8 in A. flavus, the deletion and complemented mutants of atg8 were generated according to the homologous recombination principle. Deletion of atg8 showed a significant decrease in conidiation, spore germination, and sclerotia formation compared to the WT and atg8^Cstrains. Additionally, aflatoxin production was found severely impaired in the ∆atg8 mutant. The stress assays demonstrated that ATG8 was important for A. flavus response to oxidative stress. The fluorescence microscopy showed increased levels of reactive oxygen species in the ∆atg8 mutant cells, and the transcriptional result also indicated that genes related to the antioxidant system were significantly reduced in the ∆atg8 mutant. We further found that ATG8 participated in regulating the pathogenicity of A. flavus on crop seeds. These results revealed the biological role of ATG8 in A. flavus, which might provide a potential target for the control of A. flavus and AFB1 biosynthesis. Full article

Background: The pathogenic fungus Candida albicans is a leading agent of death in immunocompromised individuals with a growing trend of antifungal resistance. Methods: The purpose is to induce resistance to drugs in a sensitive C. albicans strain followed by whole-genome sequencing to determine mechanisms of resistance. Strains will be assayed for pathogenicity attributes such as ergosterol and chitin content, growth rate, virulence, and biofilm formation. Results: We observed sequential increases in ergosterol and chitin content in fluconazole-resistant isolates by 78% and 44%. Surface thickening prevents the entry of the drug, resulting in resistance. Resistance imposed a fitness trade-off that led to reduced growth rates, biofilm formation, and virulence in our isolates. Sequencing revealed mutations in genes involved in resistance and pathogenicity such as ERG11, CHS3, GSC2, CDR2, CRZ2, and MSH2. We observed an increase in the number of mutations in key genes with a sequential increase in drug-selective pressures as the organism increased its odds of adapting to inhospitable environments. In ALS4, we observed two mutations in the susceptible strain and five mutations in the resistant strain. Conclusion: This is the first study to induce resistance followed by genotypic and phenotypic analysis of isolates to determine mechanisms of drug resistance. Full article