Multicriteria decision making attributes and estimation of physicochemical properties of kidney cancer drugs via topological descriptors.

Based on topological descriptors, QSPR analysis is an incredibly helpful statistical method for examining many physical and chemical properties of compounds without demanding costly and time-consuming laboratory tests. Firstly, we discuss and provide research on kidney cancer drugs using topological indices and done partition of the edges of kidney cancer drugs which are based on the degree. Secondly, we examine the attributes of nineteen drugs casodex, eligard, mitoxanrone, rubraca, and zoladex, etc and among others, using linear QSPR model. The study in the article not only demonstrates a good correlation between TIs and physical characteristics with the QSPR model being the most suitable for predicting complexity, enthalpy, molar refractivity, and other factors and a best-fit model is attained in this study. This theoretical approach might benefit chemists and professionals in the pharmaceutical industry to forecast the characteristics of kidney cancer therapies. This leads towards new opportunities to paved the way for drug discovery and the formation of efficient and suitable treatment options in therapeutic targeting. We also employed multicriteria decision making techniques like COPRAS and PROMETHEE-II for ranking of said disease treatment drugs and physicochemical characteristics.

TimeTector: A Twin-Branch Approach for Unsupervised Anomaly Detection in Livestock Sensor Noisy Data (TT-TBAD).

Unsupervised anomaly detection in multivariate time series sensor data is a complex task with diverse applications in different domains such as livestock farming and agriculture (LF&A), the Internet of Things (IoT), and human activity recognition (HAR). Advanced machine learning techniques are necessary to detect multi-sensor time series data anomalies. The primary focus of this research is to develop state-of-the-art machine learning methods for detecting anomalies in multi-sensor data. Time series sensors frequently produce multi-sensor data with anomalies, which makes it difficult to establish standard patterns that can capture spatial and temporal correlations. Our innovative approach enables the accurate identification of normal, abnormal, and noisy patterns, thus minimizing the risk of misinterpreting models when dealing with mixed noisy data during training. This can potentially result in the model deriving incorrect conclusions. To address these challenges, we propose a novel approach called "TimeTector-Twin-Branch Shared LSTM Autoencoder" which incorporates several Multi-Head Attention mechanisms. Additionally, our system now incorporates the Twin-Branch method which facilitates the simultaneous execution of multiple tasks, such as data reconstruction and prediction error, allowing for efficient multi-task learning. We also compare our proposed model to several benchmark anomaly detection models using our dataset, and the results show less error (MSE, MAE, and RMSE) in reconstruction and higher accuracy scores (precision, recall, and F1) against the baseline models, demonstrating that our approach outperforms these existing models.

Efficient Selective Carbon Dioxide Separation via Task-Specific Ionic Liquids Incorporated in ZIF-8.

Owing to the rapid increase in anthropogenic emission of carbon dioxide (CO2) in the atmosphere, which has resulted in a number of global climate challenges, a decrease in CO2 emissions is urgently needed in the current scenario. This study focuses on the development and characterization of composites for carbon dioxide (CO2) separation. The composites consist of two task-specific ionic liquids (TSILs), namely, tetramethylgunidinium imidazole [TMGHIM] and tetramethylgunidinium phenol [TMGHPhO], impregnated in ZIF-8. The performance of CO2 separation, including sorption capacity and selectivity, was evaluated for pristine ZIF-8 and composites of TMGHIM@ZIF-8 and TMGHPhO@ZIF-8. To demonstrate the thermal stability of the material, thermogravimetric analysis (TGA) was performed. Additionally, powder X-ray diffraction (XRD) and scanning electron microscopy (SEM) were utilized to showcase the crystal structures and morphology. Fourier transform infrared spectroscopy (FTIR) and BET were also utilized to confirm the successful incorporation of TSILs into ZIF-8. The composite synthesized with TMGHIM@ZIF-8 demonstrated superior CO2 sorption performance as compared with TMGHPhO@ZIF-8. This is attributed to its strong attraction toward CO2, resulting in a higher CO2/CH4 selectivity of 110 while pristine MOFs showed 12 that is 9 times higher than that of the pristine ZIF-8. These TSILs@ZIF-8 composites have significant potential in designing sorbent materials for efficient acid gas separation applications.

Plant extract preparation and green synthesis of silver nanoparticles using Swertia chirata: Characterization and antimicrobial activity against selected human pathogens.

Herbal medicinal plants have been used for centuries in traditional medicine, and it is interesting to see how modern research has identified the active compounds responsible for their therapeutic effects. The green synthesis of silver nanoparticles using herbal medicinal plants, such as Swertia chirata, is particularly noteworthy due to its antimicrobial properties. In the current study, the Swertia chirata plant was collected for the first time from the region of Murree, Punjab, Pakistan. After collection, extracts were prepared in different solvents (ethanol, methanol, chloroform, and distilled water), and silver nanoparticles were synthesized by reducing silver nitrate (AgNO3). The UV-visible spectrophotometer, SEM, and EDX were used to characterize the synthesized nanoparticles in terms of their size and shape. The phytochemical analysis of crude extract was performed to determine the presence of different kinds of phytochemicals. The antibacterial activity of plant extracts and the silver nanoparticles were then assessed using the agar well diffusion method against various pathogenic bacteria. The results showed that the plant contains several phytochemicals with remarkable antioxidant potential. The antibacterial analysis revealed that silver nanoparticles and the plant extracts exhibited a significant zone of inhibition against human pathogenic bacteria (Escherichia coli, S. capitis, B. subtilis, and Pseudomonas aeruginosa) as compared to the cefixime and norfloxacin. This implies that the nanoparticles have the potential to be used in nano-medicine applications, such as drug delivery systems, as well as for their antibacterial, antifungal, and antiviral activities. Additionally, the development and application of materials and technologies at the nanometer scale opens possibilities for the creation of novel drugs and therapies. Overall, the study highlights the promising potential of herbal medicinal plants found in Murree, Punjab, Pakistan, and green-synthesized silver nanoparticles in various fields of medicine and nanotechnology.

Epigenetic disruption of the RARγ complex impairs its function to bookmark AR enhancer interactions required for enzalutamide sensitivity in prostate cancer.

The current study in prostate cancer (PCa) focused on the genomic mechanisms at the cross-roads of pro-differentiation signals and the emergence of lineage plasticity. We explored an understudied cistromic mechanism involving RARγ's ability to govern AR cistrome-transcriptome relationships, including those associated with more aggressive PCa features. The RARγ complex in PCa cell models was enriched for canonical cofactors, as well as proteins involved in RNA processing and bookmarking. Identifying the repertoire of miR-96 bound and regulated gene targets, including those recognition elements marked by m6A, revealed their significant enrichment in the RARγ complex. RARγ significantly enhanced the AR cistrome, particularly in active enhancers and super-enhancers, and overlapped with the binding of bookmarking factors. Furthermore, RARγ expression led to nucleosome-free chromatin enriched with H3K27ac, and significantly enhanced the AR cistrome in G2/M cells. RARγ functions also antagonized the transcriptional actions of the lineage master regulator ONECUT2. Similarly, gene programs regulated by either miR-96 or antagonized by RARγ were enriched in alternative lineages and more aggressive PCa phenotypes. Together these findings reveal an under-investigated role for RARγ, modulated by miR-96, to bookmark enhancer sites during mitosis. These sites are required by the AR to promote transcriptional competence, and emphasize luminal differentiation, while antagonizing ONECUT2.

Taxonomic study and diversity of Postia s.lat. in Swat, Pakistan: addition of five brown rot Polypores to the country.

Brown rot Polypores are ecologically significant as they play a crucial role in maintaining the carbon cycle and contribute to humus formation in forest ecosystems through their lignocellulose degradation ability. It is important to note that some species can significantly impact timber, potentially causing decay in economically valuable wood. Many Asian countries including Pakistan are still under the exploratory phase and have undocumented species diversity in Polypore fungi. In the current study, collections representing five different species belonging to two families, Postiaceae and Adustoporiaceae, were subjected to detailed morphoanatomical and molecular analyses. A combined matrix of two gene datasets (ITS and nrLSU) was analyzed using three different phylogenetic methods viz. Maximum Parsimony (MP), Maximum Likelihood (ML), and Bayesian inference (BI). Our study presents descriptions of five previously undocumented brown rot Polypore species from the country including Fuscopostia fragilis (Fr.) B.K. Cui, L.L. Shen & Y.C. Dai, Amaropostia stiptica (Pers.) B.K. Cui, L.L. Shen & Y.C. Dai, Cyanosporus piceicola B.K. Cui, L.L. Shen & Y.C. Dai, Spongiporus balsameus (Peck) A. David, Rhodonia placenta (Fr.) Niemelä, K.H. Larss. & Schigel. Regarding the molecular data, nodes of our subject sequences were substantially supported and fell under their respective species clades with high ML bootstrap values (≥ 95), MP bootstrap ≥ 74 and BI probabilities ≥ 0.98. Findings of the study will not only contribute to our understanding of local Polypores species diversity but also enhance knowledge of geographical distribution in global context.

Ce-doped ZnO nanostructures: A promising platform for NO2 gas sensing.

In this comprehensive study, Ce-doped ZnO nanostructures were hydrothermally synthesized with varying Ce concentrations (0.5%, 1.0%, 1.5%, and 2.0%) to explore their gas-sensing capabilities, particularly towards NO2. Structural characterization revealed that as Ce doping increased, crystal size exhibited a slight increment while band gap energies decreased. Notably, the 0.5% Ce-doped ZnO nanostructure demonstrated the highest NO2 gas response of 8.6, underscoring the significance of a delicate balance between crystal size and band gap energy for optimal sensing performance. The selectivity of the 0.5% Ce-doped ZnO nanostructures to NO2 over other gases like H2, acetone, NH3, and CO at a concentration of 100 ppm and an optimized temperature of 250 °C was exceptional, highlighting its discriminatory prowess even in the presence of potential interfering gases. Furthermore, the sensor displayed reliability and reversibility during five consecutive tests, showcasing consistent performance. Long-term stability testing over 30 days revealed that the gas response remained almost constant, indicating the sensor's remarkable durability. In addition to its robustness against humidity variations, maintaining effectiveness even at 41% humidity, the sensor exhibited impressive response and recovery times. While the response time was swift at 11.8 s, the recovery time was slightly prolonged at 56.3 s due to the strong adsorption of NO2 molecules onto the sensing material hindering the desorption process. The study revealed the intricate connection between Ce-doping levels, structure, and gas-sensing. It highlighted the 0.5% Ce-doped ZnO nanostructure as a highly selective, reliable, and durable NO2 gas sensor, with implications for future environmental monitoring and safety.

Selective efficient photocatalytic degradation of antibiotics and direct Z-type migration pathway for hierarchical core-shell TiO2/g-C3N4 composites.

Constructing superior Z-type photocatalytic heterojunction is beneficial to effectively enlarge interface contact, improve the photo-generated carrier separation rate, and retain the high redox ability. In this work, we designed a hierarchical core-shell g-C3N4/TiO2 structure to build Z-type heterojunction via combining simple template method and pyrolysis process. A close-knit Z-type heterojunction was constructed using TiO2 as a thick core and g-C3N4 as an ultra-thin shell. The effects of lamp source, wavelength, tetracycline (TC) concentration, and photocatalyst dose on the degradation performance on TC of g-C3N4/TiO2 were inspected. 0.1TiO2/g-C3N4 photocatalyst had the best degradation rate and highest removal rate within 30 min, and its degradation rate was about 49, 23, and 5 times than pure g-C3N4, TiO2, and commercial TiO2/g-C3N4 in respect. Moreover, compared with degradation ability under Xenon lamp, LED irradiation for g-C3N4/TiO2 composites showed a remarkable selective degradation. The fast and efficient Z-type transfer pathway of 0.1 g-C3N4/TiO2 was realized by forming an optimized interface and abundant surface active sites ascribed to the combined action of thick TiO2 core and ultra-thin g-C3N4 shell. In addition, the degradation intermediates were analyzed by LC-MS and suggested pathways of degradation. The work could provide novel design concept to obtain reliable Z-type photocatalysts with hierarchical core-shell structure applied in degradation of antibiotic wastewater.

An estimation of physiochemical properties of bladder cancer drugs via degree-based chemical bonding topological descriptors.

The use of topological descriptors remains a significant approach due to numerous advances in the field of drug design. Descriptors provide numerical representations of a molecule's chemical characteristics when used with QSPR models. The QSPR analysis for bladder medications is the main focus of this study. Linear regression model is developed for the computed indices values, the physicochemical properties of the bladder medications are examined.Communicated by Ramaswamy H. Sarma.

Towards enhancing security of IoT-Enabled healthcare system.

The Internet-of-Things (IoT)-based healthcare systems are comprised of a large number of networked medical devices, wearables, and sensors that collect and transmit data to improve patient care. However, the enormous number of networked devices renders these systems vulnerable to assaults. To address these challenges, researchers advocated reducing execution time, leveraging cryptographic protocols to improve security and avoid assaults, and utilizing energy-efficient algorithms to minimize energy consumption during computation. Nonetheless, these systems still struggle with long execution times, assaults, excessive energy usage, and inadequate security. We present a novel whale-based attribute encryption scheme (WbAES) that empowers the transmitter and receiver to encrypt and decrypt data using asymmetric master key encryption. The proposed WbAES employs attribute-based encryption (ABE) using whale optimization algorithm behaviour, which transforms plain data to ciphertexts and adjusts the whale fitness to generate a suitable master public and secret key, ensuring security against unauthorized access and manipulation. The proposed WbAES is evaluated using patient health record (PHR) datasets collected by IoT-based sensors, and various attack scenarios are established using Python libraries to validate the suggested framework. The simulation outcomes of the proposed system are compared to cutting-edge security algorithms and achieved finest performance in terms of reduced 11 s of execution time for 20 sensors, 0.121 mJ of energy consumption, 850 Kbps of throughput, 99.85 % of accuracy, and 0.19 ms of computational cost.

The MYC axis in advanced prostate cancer is impacted through concurrent targeting of ERß and AR using a novel ERß-selective ligand alongside Enzalutamide.

We have dissected the role of Estrogen receptor beta (ERß) in prostate cancer (PCa) with a novel ERß ligand, OSU-ERb-12. Drug screens revealed additive interactions between OSU-ERB-12 and either epigenetic inhibitors or the androgen receptor antagonist, Enzalutamide (Enza). Clonogenic and cell biolody studies supported the potent additive effects of OSU-ERB-12 (100nM) and Enza (1µM). The cooperative behavior was in PCa cell lines treated with either OSU-ERB-12 plus Enza or combinations involving 17ß-estradiol (E2). OSU-ERb-12 plus Enza uniquely impacted the transcriptiome, accessible chromatin, and the AR, MYC and H3K27ac cistromes. This included skewed transcriptional responses including suppression of the androgen and MYC transcriptomes, and repressed MYC protein. OSU-ERb-12 plus Enza uniquely impacted chromatin accessibility at approximately 3000 nucleosome-free sites, enriched at enhancers, enriched for basic Helix-Loop-Helix motifs. CUT&RUN experiments revealed combination treatment targeting of MYC, AR, and H3K27ac again shaping enhancer accessibility. Specifically, it repressed MYC interactions at enhancer regions enriched for bHLH motifs, and overlapped with publicly-available bHLH cistromes. Finally, cistrome-transcriptome analyses identified ~200 genes that distinguished advanced PCa tumors in the SU2C cohort with high androgen and low neuroendocrine scores.

Layered Architectural Fabrication of a Novel Sulfite Nanobiosensor by Encapsulation of Sulfite Oxidase on a Polypyrrole-Multiwalled Carbon Nanotubes Composite Decorated with Platinum Nanoparticles.

The fabrication of a highly selective and ultrasensitive sulfite nanobiosensor based on a layered architectural fabrication aided by the encapsulation of sulfite oxidase (SOx) in Nafion (Naf) matrix on a multiwalled carbon nanotubes-polypyrrole (MWCNTs-PPy) composite decorated with platinum nanoparticles (PtNPs) is described. The MWCNTs are deposited in the inner layer on a Pt electrode during electropolymerization of pyrrole (Py), followed by decoration with a PtNPs layer and subsequent encapsulation of SOx with Naf in the third layer capped with a fourth thin PtNPs layer. Images obtained by field emission scanning electron microscopy (FESEM) reveal that high-density PtNPs are deposited onto the 3D nanostructured inner MWCNTs-PPy layer and the electrochemical behavior is investigated. A large surface area provided by the incorporation of MWCNTs in the composite and decoration with PtNPs enables increased SOx loading, SOx retention, and substantial improvement in sensing performance. The resulting layered PtNPs/SOx-Naf/PtNPs/MWCNTs-PPy nanobiosensor exhibits a fast response time (within 3 s), a linear calibration range of 20 nmm - 6 m with an excellent sensitivity of 71 µA mm-1  cm-2 and a detection limit of 5.4 nm. The nanobiosensor  was effective in discriminating against common interferants and  was successfully applied to sulfite determination in real samples.

Realizing the Ultralow Lattice Thermal Conductivity of Cu3SbSe4 Compound via Sulfur Alloying Effect.

Cu3SbSe4 is a potential p-type thermoelectric material, distinguished by its earth-abundant, inexpensive, innocuous, and environmentally friendly components. Nonetheless, the thermoelectric performance is poor and remains subpar. Herein, the electrical and thermal transport properties of Cu3SbSe4 were synergistically optimized by S alloying. Firstly, S alloying widened the band gap, effectively alleviating the bipolar effect. Additionally, the substitution of S in the lattice significantly increased the carrier effective mass, leading to a large Seebeck coefficient of ~730 µVK-1. Moreover, S alloying yielded point defect and Umklapp scattering to significantly depress the lattice thermal conductivity, and thus brought about an ultralow κlat ~0.50 Wm-1K-1 at 673 K in the solid solution. Consequently, multiple effects induced by S alloying enhanced the thermoelectric performance of the Cu3SbSe4-Cu3SbS4 solid solution, resulting in a maximum ZT value of ~0.72 at 673 K for the Cu3SbSe2.8S1.2 sample, which was ~44% higher than that of pristine Cu3SbSe4. This work offers direction on improving the comprehensive TE in solid solutions via elemental alloying.

High-performance circular polarization modulation using a dielectric metasurface.

We demonstrate a chiral metasurface that exhibits a giant chiroptical response as well as functions as an optical diode due to geometrical asymmetry for circularly polarized light (CPL). Engineering the Mie-type multipole radiation using geometrical features led to performance values in terms of near-unity transmission and circular dichroism (CD) efficiency (about 0.96) and an extinction ratio of  ∼3.8×104 for 1550 nm wavelength. A continuous stopband of 1538-1556 nm is achieved for an unchosen component of CPL while keeping the transmission efficiency of the chosen CPL component larger than 0.9. Because of the high extinction ratio and CD efficiency, the proposed metasurface has the potential for chiroptical applications including high-contrast polarization imaging, precise Stokes parameters measurement, optical diodes, and polarization detection for CPL.

How various stakeholder pressure influences mega-project sustainable performance through corporate social responsibility and green competitive advantage.

Although numerous research studies have revealed that mega-projects are closely linked to globalization and civilization, few researchers have performed logical assessments of mega-projects using stakeholder theory. As stakeholders demand greater sustainability in the construction industry, sustainable development (SD) has become a priority. However, corporate social responsibility (CSR) and green competitive advantage (GCA) have often been overlooked. This study aims to fill this knowledge gap by creating a comprehensive model to predict mega-project sustainable performance (MSP). Data was collected from 289 respondents in Pakistan's construction industry, and hypotheses were tested using partial least squares structural equation modeling and fuzzy set qualitative comparative analysis. The results indicate that both secondary and primary stakeholders' pressure positively impacts CSR and MSP. Moreover, CSR significantly affects GCA and MSP, with CSR and GCA partially mediating these relationships. Thus, the proposed model could offer innovative insights for decision-makers and engineering managers, recommend adopting social and green practices to enhance MSP with the support of concerned stakeholders' pressure, and help achieve SD objectives.

Utilizing the intelligence edge framework for robotic upper limb rehabilitation in home.

Robotic devices are gaining popularity for the physical rehabilitation of stroke survivors. Transition of these robotic systems from research labs to the clinical setting has been successful, however, providing robot-assisted rehabilitation in home settings remains to be achieved. In addition to ensure safety to the users, other important issues that need to be addressed are the real time monitoring of the installed instruments, remote supervision by a therapist, optimal data transmission and processing. The goal of this paper is to advance the current state of robot-assisted in-home rehabilitation. A state-of-the-art approach to implement a novel paradigm for home-based training of stroke survivors in the context of an upper limb rehabilitation robot system is presented in this paper. First, a cost effective and easy-to-wear upper limb robotic orthosis for home settings is introduced. Then, a framework of the internet of robotics things (IoRT) is discussed together with its implementation. Experimental results are included from a proof-of-concept study demonstrating that the means of absolute errors in predicting wrist, elbow and shoulder angles are 0.89180,2.67530 and 8.02580, respectively. These experimental results demonstrate the feasibility of a safe home-based training paradigm for stroke survivors. The proposed framework will help overcome the technological barriers, being relevant for IT experts in health-related domains and pave the way to setting up a telerehabilitation system increasing implementation of home-based robotic rehabilitation. The proposed novel framework includes:•A low-cost and easy to wear upper limb robotic orthosis which is suitable for use at home.•A paradigm of IoRT which is used in conjunction with the robotic orthosis for home-based rehabilitation.•A machine learning-based protocol which combines and analyse the data from robot sensors for efficient and quick decision making.

Exploring the gas-sensing properties of MOF-derived TiN@CuO as a hydrogen sulfide sensor.

In an effort to develop a long-lasting gas sensor, this article presents titanium nitride (TiN) as a potential substitute sensitive material in conjunction with (copper(II) benzene-1,3,5-tricarboxylate) Cu-BTC-derived CuO. The work focused on the gas-sensing characteristics of TiN/CuO nanoparticles in detecting H2S gas at various temperatures and concentrations. XRD, XPS, and SEM were utilized to analyze the composites with varied Cu molar ratios. The responses of TiN/CuO-2 nanoparticles to 50 and 100 ppm H2S gas at 50 °C and 250 °C are 34.8 and 60.0, respectively. The related sensor had high selectivity and stability towards H2S, and the response of TiN/CuO-2 is still 2.5-5 ppm H2S. The gas-sensing properties as well as the mechanism are fully explained in this study. TiN/CuO might be a choice for the detection of H2S gas, opening up new avenues for applications in industries, medical facilities, and homes.

Biofunctionalisation of Polypyrrole Nanowires Array with Sulfite Oxidase Coupled with the Integration of Platinum Nanoparticles for Ultrasensitive Amperometric Detection of Sulfite.

Sulfite determination in foods and alcoholic beverages is a common requirement by food and drug administration organisations in most countries. In this study, the enzyme, sulfite oxidase (SOx), is used to biofunctionalise a platinum-nanoparticle-modified polypyrrole nanowire array (PPyNWA) for the ultrasensitive amperometric detection of sulfite. A dual-step anodisation method was used to prepare the anodic aluminum oxide membrane used as a template for the initial fabrication of the PPyNWA. PtNPs were subsequently deposited on the PPyNWA by potential cycling in a platinum solution. The resulting PPyNWA-PtNP electrode was then biofuntionalised by adsorption of SOx onto the surface. The confirmation of the adsorption of SOx and the presence of PtNPs in the PPyNWA-PtNPs-SOx biosensor was verified by scanning electron microscopy and electron dispersive X-ray spectroscopy. Cyclic voltammetry and amperometric measurements were used to investigate the properties of the nanobiosensor and to optimise its use for sulfite detection. Ultrasensitive detection of sulfite with the PPyNWA-PtNPs-SOx nanobiosensor was accomplished by use of 0.3 M pyrrole, 10 U mL-1 of SOx, adsorption time of 8 h, a polymerisation period of 900 s, and an applied current density of 0.7 mA cm-2. The response time of the nanobiosensor was 2 s, and its excellent analytical performance was substantiated with a sensitivity of 57.33 µA cm-2 mM-1, a limit of detection of 12.35 nM, and a linear response range from 0.12 to 1200 µM. Application of the nanobiosensor to sulfite determination in beer and wine samples was achieved with a recovery efficiency of 97-103%.

Validation of Fuscoporia (Hymenochaetales, Basidiomycota) ITS sequences and five new species based on multi-marker phylogenetic and morphological analyses.

Although there is a continuous increase in available molecular data, not all sequence identities in public databases are always properly verified and managed. Here, the sequences available in GenBank for Fuscoporia (Hymenochaetales) were validated. Many morphological characters of Fuscoporia overlap among the species, emphasizing the role of molecular identification for accuracy. The identities of 658 Fuscoporia GenBank internal transcribed spacer (ITS) sequences were assessed using ITS phylogeny, revealing 109 (16.6%) misidentified and 196 (29.8%) unspecified sequences. They were validated and re-identified based on the research articles they were published in and, if unpublished, based on sequences from the type, type locality-derived sequences, or otherwise reliable sequences. To enhance the resolution of species delimitation, a phylogenetic assessment of a multi-marker dataset (ITS + nrLSU + rpb2 + tef1) was conducted. The multi-marker phylogeny resolved five of the twelve species complexes found in the ITS phylogeny and uncovered five new Fuscoporia species: F. dolichoseta, F. gilvoides, F. koreana, F. reticulata, and F. semicephala. The validated ITS sequences in this study may prevent further accumulation of misidentified sequences in public databases and contribute to a more accurate taxonomic evaluation of Fuscoporia species.