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The faculty of engineering at McMaster University is very diverse with students coming from a variety of socio-economic backgrounds and nationalities. There is an expected level of prerequisite knowledge for courses in the program, especially for subjects in mathematics and physics. Yet, a significant number of students struggle to reach the same level of prior knowledge as their peers due to a lack of educational resources or due to language barriers. Entering lectures without the expected baseline understanding of the concepts increases the risk of cognitive overload because these students exert additional mental effort in retaining the pre-lecture information along with the lecture content. As a solution to this problem, we present a suite of web-based interactive programs that are accessible to the students outside the class. The Software Suite will provide supplementary material to assist with self-paced learning in a 3rd year undergraduate engineering course, i.e., Finite Element Analysis, at McMaster University's W Booth School of Engineering Practice and Technology. It will enable students design and analyze various engineering applications, namely, Spring System, Trusses, Beams, Frames, and Heat Transfer along one or two dimensions. The purpose of the interactive platform with several programs is to actively engage the students with this cognitive tool to cement their understanding of the concepts instead of passively perceiving it as a tutor or repository of information. [ABSTRACT FROM AUTHOR]

The ambient stability of α-FAPbI3 perovskite remains one of the biggest barriers to its commercialization, despite many attempts to enhance its lifetime. Due to the difficulties in experimentally investigating the transition kinetics, numerical simulation was performed. Surprising results were uncovered that the unstable α phase could be maintained in ambient conditions under compression, caused by the reduced Gibbs free energy of this phase. By analysing the transition rate, the detailed kinetic parameters have also been obtained, enabling us to construct a more complete phase map as a function of temperature and stress, offering a possible path towards stable high PCE perovskite solar devices, which opens an unprecedented avenue in perovskite solar cell research, and will hopefully be of intrinsic interest to the broad materials research community as well. [ABSTRACT FROM AUTHOR]

[Objective] This study aimed to explore the mechanism of action between Amomum villosum polysaccharide (AVP) and wheat starch and reveal the dose-effect relationship of AVP on the quality of wheat starch. [Methods] an AVP-wheat starch compound system with different concentrations of AVP was prepared. The effects of different concentrations of AVP on the gelatinization characteristics, rheological properties, thermodynamic properties, crystal structure and digestion characteristics of wheat starch were studied. [Results] The AVP could increase the viscosity and gelatinization temperature of the wheat starch compound system, reduce the leaching of amylose during gelatinization and the damage degree of the crystalline region during wheat starch gelatinization, and delay the gelatinization process. When the concentration of AVP was 1.00%, the disintegration value of the compound system was 299 mPa·s, the retrogradation value was 532 mPa·s, and the gelatinization enthalpy was 666.29 J/g, indicating that the anti-aging effect and the stability were the best. Fourier infrared spectrum analysis showed that there was a hydrogen bond interaction between AVP and wheat, and the bond was the strongest when the mass concentration of AVP was 1.00%. The results of in vitro simulated digestion showed that AVP could inhibit the digestion of wheat starch. [Conclusion] Adding AVP can effectively improve the thermal stability of wheat starch and reduce the digestibility of wheat starch.

Scrophularia ningpoensis Hemsl. (SN) is an herbal medicine used as a functional food in China. SN has traditionally been used to treat diabetes mellitus (DM), but its mechanism of action is not well understood. Our previous study indicated that the aqueous extract of SN can reduce hepatic insulin resistance and correct the irregular shape of pancreatic islets in diabetic mice. This study aims to investigate whether the aqueous extract of SN can regulate pyroptosis in pancreatic β-cells and explore its underlying mechanisms. Db/db mice were orally given an aqueous extract of SN for eight weeks. Subsequently, their pancreatic tissues were collected for histopathological analysis and immunoblotting. Rat insulinoma (INS-1) cells were cultured either alone or with the aqueous extract of SN and evaluated for cell viability, pyroptotic body formation, AMP-activated protein kinase (AMPK) activity, the NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) inflammasome and gasdermin D (GSDMD) activation, and reactive oxygen species (ROS) production under high glucose (HG) exposure conditions. The aqueous extract of SN reduced insulitis and pancreatic β-cell death in db/db mice. Increased AMPK phosphorylation and decreased NLRP3 inflammasome and GSDMD activation were observed in pancreatic tissues after administration of the aqueous extract of SN. In vitro, the aqueous extract of SN increased cell viability and AMPK phosphorylation in a concentration-dependent manner. Additionally, the aqueous extract of SN corrected excessive ROS generation, NLRP3 inflammasome and GSDMD activation, and pyroptotic body formation. Inhibition of AMPK negated these beneficial effects of the aqueous extract of SN on INS-1 cells. The study concluded that the aqueous extract of SN alleviates β-cell pyroptosis by inhibiting NLRP3/GSDMD activation in an AMPK-dependent manner.

Growth factor-derived peptides are bioactive molecules that play a crucial role in various physiological processes within the human body. Over the years, extensive research has revealed their diverse applications, ranging from antimicrobial properties to their potential in neuroprotection and treating various diseases. These peptides exhibit innate immune responses and have been found to possess potent antimicrobial properties against a wide range of pathogens. Growth factor-derived peptides have demonstrated the ability to promote neuronal survival, prevent cell death, and stimulate neural regeneration. As a result, they hold immense promise in the treatment of various neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and multiple sclerosis, as well as in the management of traumatic brain injuries. Moreover, growth factor-derived peptides have shown potential for supporting tissue repair and wound healing processes. By enhancing cell proliferation and migration, these peptides contribute to the regeneration of damaged tissues and promote a more efficient healing response. The applications of growth factor-derived peptides extend beyond their therapeutic potential in health; they also have a role in various disease conditions. For example, researchers have explored their influence on cancer cells, where some peptides have demonstrated anti-cancer properties, inhibiting tumor growth and promoting apoptosis in cancer cells. Additionally, their immunomodulatory properties have been investigated for potential applications in autoimmune disorders. Despite the immense promise shown by growth factor-derived peptides, some challenges need to be addressed. Nevertheless, ongoing research and advancements in biotechnology offer promising avenues to overcome these obstacles. The review summarizes the foundational biology of growth factors and the intricate signaling pathways in various physiological processes as well as diseases such as cancer, neurodegenerative disorders, cardiovascular ailments, and metabolic syndromes.

Background: To systematically evaluate the relationship between the expression level of long noncoding RNA NEAT1 and the clinical characteristics and prognostic value of rectal cancer patients. Methods: PubMed, EMBASE, Cochrane library database and case-control studies on the correlation between abnormal expression of lncRNA NEAT1 and prognosis of rectal cancer patients published by the American clinical trials registry before May 1, 2023 were searched. The search time was from the establishment of the database to May 30, 2023. Results: A total of 7 case-control studies were included, including 1063 cancer patients. The results of meta-analysis showed that the high expression of lncRNA NEAT1 was significantly correlated with the degree of differentiation [or=0.45, 95%CI=0.32-0.63, P

Abstract Background Mitochondrial genome abnormalities can lead to mitochondrial dysfunction, which in turn affects cellular biology and is closely associated with the development of various diseases. The demand for mitochondrial DNA (mtDNA) sequencing has been increasing, and Illumina and MGI are two commonly used sequencing platforms for capture-based mtDNA sequencing. However, there is currently no systematic comparison of mtDNA sequencing performance between these two platforms. To address this gap, we compared the performance of capture-based mtDNA sequencing between Illumina's NovaSeq 6000 and MGI's DNBSEQ-T7 using tissue, peripheral blood mononuclear cell (PBMC), formalin-fixed paraffin-embedded (FFPE) tissue, plasma, and urine samples. Results Our analysis indicated a high degree of consistency between the two platforms in terms of sequencing quality, GC content, and coverage. In terms of data output, DNBSEQ-T7 showed higher rates of clean data and duplication compared to NovaSeq 6000. Conversely, the amount of mtDNA data obtained by per gigabyte sequencing data was significantly lower in DNBSEQ-T7 compared to NovaSeq 6000. In terms of detection mtDNA copy number, both platforms exhibited good consistency in all sample types. When it comes to detection of mtDNA mutations in tissue, FFPE, and PBMC samples, the two platforms also showed good consistency. However, when detecting mtDNA mutations in plasma and urine samples, significant differenceof themutation number detected was observed between the two platforms. For mtDNA sequencing of plasma and urine samples, a wider range of DNA fragment size distribution was found in NovaSeq 6000 when compared to DNBSEQ-T7. Additionally, two platforms exhibited different characteristics of mtDNA fragment end preference. Conclusions In summary, the two platforms generally showed good consistency in capture-based mtDNA sequencing. However, it is necessary to consider the data preferences generated by two sequencing platforms when plasma and urine samples were analyzed.

Abstract Background In the past quite a long time, intraoperative cholangiography(IOC)was necessary during laparoscopic cholecystectomy (LC). Now magnetic resonance cholangiopancreatography (MRCP) is the main method for diagnosing common bile duct stones (CBDS). Whether MRCP can replace IOC as routine examination before LC is still inconclusive. The aim of this study was to analyze the clinical data of patients undergoing LC for cholecystolithiasis, and to explore the necessity and feasibility of preoperative routine MRCP in patients with cholecystolithiasis. Methods According to whether MRCP was performed before operation, 184 patients undergoing LC for cholecystolithiasis in the Department of General Surgery, Beijing Shijitan Hospital, Capital Medical University from January 1, 2017 to December 31, 2018 were divided into non-MRCP group and MRCP group for this retrospective study. The results of preoperative laboratory test, abdominal ultrasound and MRCP, biliary related comorbidities, surgical complications, hospital stay and hospitalization expenses were compared between the two groups. Results Among the 184 patients, there were 83 patients in non-MRCP group and 101 patients in MRCP group. In MRCP group, the detection rates of cholecystolithiasis combined with CBDS and common bile duct dilatation by MRCP were higher than those by abdominal ultrasound (P 0.05), but there was significant difference in hospitalization expenses (P 0.05). Conclusions The preoperative MRCP can detect CBDS, cystic duct stones and anatomical variants of biliary tract that cannot be diagnosed by abdominal ultrasound, which is helpful to plan the surgical methods and reduce the surgical complications. From the perspective of health economics, routine MRCP in patients with cholecystolithiasis before LC does not increase hospitalization costs, and is necessary and feasible.

Abstract Objective Clinical approaches to analgesia following total shoulder arthroplasty include liposomal bupivacaine, local infiltration analgesia, single-shot interscalene block, and continuous interscalene block. However, the best method remains contentious. This study conducts a network meta-analysis comparing these four methods, aiming to identify the most effective analgesic approach. Methods Randomized controlled trials on analgesic regimens for total shoulder arthroplasty were identified through searches of PUBMED, Cochrane Central Register of Controlled Trials, EMBASE, Web of Science, and Scopus databases, covering their inception through November 2023. Network meta-analysis was performed using STATA 15.1, and the Cochrane Handbook version 5.1.0 risk of bias tool was employed for quality assessment of the literature. Results Twelve randomized controlled trials were included, comprising 1537 patients undergoing total shoulder arthroplasty. The interventions compared were ssISB, cISB, LIA, and LB. Regarding the quality of the literature, four studies were deemed low risk, one high risk, and seven moderate risk. The network meta-analysis revealed that in terms of VAS scores in the PACU, the ssISB group was the most effective, followed by cISB and LB, with LIA being the least effective. This pattern continued in VAS scores on the first and second postoperative days. Regarding morphine consumption, the cISB group showed the most significant reduction in the PACU and on the first postoperative day, while the LIA group performed best in total postoperative morphine consumption. The shortest average hospital stay was noted in the cISB group. Conclusion The ssISB method excels in controlling early postoperative pain, particularly during the PACU stage and early postoperative period. Additionally, the cISB method is notable for reducing postoperative morphine consumption and shortening average hospital stays. While the LIA method ranks first in reducing total morphine consumption, it is weaker in pain control. The LB method is underwhelming across most assessment parameters. These findings underscore the importance of selecting appropriate analgesic strategies for different postoperative recovery phases and provide valuable insights for clinicians to optimize postoperative pain management. Furthermore, they suggest a need for future research to explore the specific application and effectiveness of these methods in varying clinical contexts.

Abstract Pearl oil apricot almonds are rich in proteins, being a valuable raw material for preparing antioxidant peptides. In this study, almond protein hydrolysates (APHs) were obtained by enzymatic hydrolysis and divided into APHs‐1 (10 kDa). APHs‐1‐c, purified from APHs‐1, was proved to show the strongest antioxidant effect through activity tracking experiments. APHs‐1‐c also can protect HepG2 cells against oxidative damage by reducing intracellular reactive oxygen species and MDA levels, elevating glutathione levels as well as increasing superoxide dismutase and catalase activities, and its protective effect is related to the Keap1–Nrf2 signaling pathway. Forty bioactive peptide sequences were identified from APHs‐1‐c, and Thr‐Glu‐Asp‐Asp‐Trp‐Arg‐Trp‐His (TEDDWRWH; P1), Trp‐Tyr‐Asp‐Asn‐Glu‐Trp‐Gly‐Tyr‐Arg (WYDNEWGYR; P2), and Ala‐Glu‐Asp‐His‐Glu‐Trp‐Trp‐Arg (AEDHEWWWR; P3) had the most potential for antioxidant activity by molecular docking studies. P1, P2, and P3 showed desirable 1,1‐diphenyl‐2‐picrylhydrazyl radical scavenging activity (IC50 = 0.634–3.381 mmol/L), 2,2′‐azino‐bis (3‐ethylbenzothiazoline‐6‐sulfonic acid) diammonium salt radical scavenging activity (IC50 = 0.221–0.309 mmol/L), and ferric‐reducing antioxidant power. These results suggested that almonds protein hydrolysates and its derived antioxidant peptides could serve as potential ingredients applied in functional foods.

Monitoring and controlling the occurrence of hematoma expansion events after a stroke is a primary clinical focus. The introduction of machine learning (ML) techniques offers intelligent decision support for physicians in this domain. However, for doctors without an ML background, the behavior of a hematoma expansion predictor seems opaque, similar to a “black box.” Moreover, the vast and diverse set of features typically present in medical data acts as a double-edged sword: while encapsulating rich information with potential value, it also includes redundant details that offer little to predictive utility. Comprehensive feature selection is crucial, but many current state-of-the-art hematoma expansion prediction studies based on ML often overlook this step. In this paper, we propose a methodology tailored for comprehensive feature selection across diverse and abundant medical data features and rigorously evaluate ML models. Through experiments on a real-world post-stroke hematoma expansion prediction dataset, we demonstrate the efficacy of our approach in enhancing the performance of ML predictors. Visualization of the associated feature selection process and results further bolsters physicians’ understanding of the model’s decision-making basis, thereby strengthening its interpretability.

Abstract The relationship between metallic micronutrients and soil microorganisms, and thereby soil functioning, has been little explored. Here, we investigate the relationship between metallic micronutrients (Fe, Mn, Cu, Zn, Mo and Ni) and the abundance, diversity and function of soil microbiomes. In a survey across 180 sites in China, covering a wide range of soil conditions the structure and function of the soil microbiome are highly correlated with metallic micronutrients, especially Fe, followed by Mn, Cu and Zn. These results are robust to controlling for soil pH, which is often reported as the most important predictor of the soil microbiome. An incubation experiment with Fe and Zn additions for five different soil types also shows that increased micronutrient concentration affects microbial community composition and functional genes. In addition, structural equation models indicate that micronutrients positively contribute to the ecosystem productivity, both directly (micronutrient availability to plants) and, to a lesser extent, indirectly (via affecting the microbiome). Our findings highlight the importance of micronutrients in explaining soil microbiome structure and ecosystem functioning.

Computing power services are a key factor for strengthening the digital capabilities and core competitiveness of China. In the context of the Digital China initiative, the computing power service system of China needs to adapt to the computing power demands of different fields, levels, and scenarios, and the reasonable allocation and efficient utilization of computing resources should be realized, thereby guiding the development and innovation of the digital economy. Based on a global perspective and China’s current situation, this study clarifies the implications of computing power services and analyzes the problems regarding the development of China’s computing power services, including prominent contradictions between supply and demand, uneven distribution of basic computing resources, lack of circulation channels for resources, non-unified technical service standards. An overall architecture for the construction of China’s computing power service system is proposed from the aspects of computing power service form basis, evolution model, and top-level design, and key strategies and development paths are explored. Furthermore, the following suggestions are proposed: (1) strengthening top-level design of computing power to promote the integrated development of computing networks; (2) optimizing computing power resource layout while lowering the threshold for using computing power; (3) building computing power sharing platforms to revitalize social computing values; (4) improving computing power utilization mechanisms and establishing computing power leasing systems; and (5) stimulating potentials in scientific and technological research by exploiting computing power talent advantages.

The real-time monitoring of the molten steel flow in a mould during continuous casting holds significant importance in enhancing a product`s quality. The variation in the meniscus velocity of molten steel during actual production directly correlates with numerous critical defects in continuous casting products. Consequently, monitoring the speed, flow direction, and meniscus velocity variation becomes crucial to adjusting the process parameters and ensuring product quality control. This study utilises the open flow test section of a liquid metal loop platform to simulate the flow field of a mould`s liquid level. The investigation focuses on assessing the accuracy and reliability of Lorentz force velocimetry (LFV) to measure the liquid metal velocity. The electromagnetic sensitive area of LFV is explored through numerical simulation, and multiple sets of measurement experiments are conducted under various flow conditions. The study examines the influence of the measurement position and flow structure on the magnetic field action area and measurement results of LFV. To validate the velocity measurements obtained in this area, Ultrasonic Doppler Velocimetry (UDV) is employed for comparison and verification. The results demonstrate that LFV can accurately measure the horizontal velocity component within a depth range of 0 to 4 mm near the surface of the open flow. The relative error compared to UDV remains below 8%, and the fixed-point measurement can be sustained for over 20 minutes. These findings affirm the reliability and industrial applicability of LFV in measuring the horizontal velocity component near the surface of molten metal.

The effects of high temperature annealing on the interface microstructure and mechanical properties of cast-rolled Ti/Al composite plates were investigated by means of SEM, EBSD, XRD, microhardness, tensile test at room temperature and T-shaped peeling test, etc. The results show that the microstructure of Ti matrix hardly changes during annealing at 550 ℃, while the Al matrix recrystallizes and begins to grow after annealing for 1 h. During the annealing process, the diffusion layer at the interface gradually thickens, and the second phase TiAl3 is generated at 15 min, and the second phase TiAl3 is connected into flakes at 1 h, and the bonding strength of the Ti/Al composite plate interface is decreased rapidly. The bonding strength of Ti/Al composite plate reaches the maximum value of 23.6 N/mm after annealing for 30 min. At 1 h annealing, the tensile strength and elongation of the cast-rolled Ti/Al composite plate reach the peak values of 236 MPa and 27.6%, respectively, which are higher than those of the cast-rolled Ti/Al composite plate.

Circadian rhythms influence various aspects of the biology and physiology of the host, such as food intake and sleep/wake cycles. In recent years, an increasing amount of genetic and epidemiological data has shown that the light/dark cycle is the main cue that regulates circadian rhythms. Other factors, including sleep/wake cycles and food intake, have necessary effects on the composition and rhythms of the gut microbiota. Interestingly, the gut microbiota can affect the circadian rhythm of hosts in turn through contact-dependent and contact-independent mechanisms. Furthermore, the gut microbiota has been shown to regulate the sleep/wake cycles through gut-brain-microbiota interaction. In addition to diabetes, the gut microbiota can also intervene in the progression of neuro- degenerative diseases through the gut-brain-microbiota interaction, and also in other diseases such as hypertension and rheumatoid arthritis, where it is thought to have a spare therapeutic potential. Even though fecal microbiota transplantation has good potential for treating many diseases, the risk of spreading intestinal pathogens should not be ignored.

Abstract Cashew nut is a globally popular nut not only for its delicious and crunchy flavor but also for bioactive compounds, which present positive benefits to human health. Different parts of cashew have characteristic compounds. The kernel of cashew nut is rich in fatty acids, the testa is rich in polyphenols, cashew apple is rich in polyphenols and carotenoids, and phenols with aliphatic long chain are present in the cashew nutshell liquid. Therefore, the edible part of cashew possesses a wide range of bioactive compounds, with reported biological properties, including anti‐tumor, brain health, cardiovascular and cerebrovascular protection, anti‐diabetic, gastroprotection, pathophysiological disorders protection, and antioxidant. On the other hand, the inedible part of cashew, the cashew nutshell liquid, could play an important role in the industry as surface coatings, insulating formulations and so on. Hence, there are considerable demands to increase the added value of cashew, thereby exploring greater economic value. Thus, this review summarizes nutrients, bioactive compounds, biological functions, and applications of Anacardium occidentale to provide a theoretical basis and inspiration for further in‐depth studies and utilization.

In order to solve the problems such as significant frequency fluctuation and slow dynamic response under load disturbance in islanded microgrid which has a diesel generator (DG) as the primary source, an auxiliary frequency regulation method is proposed to improve the dynamic response process of the system. Firstly, the model of diesel generator system is established to analyze the impact on transient state due to main parameters, including inertia and response delay. Secondly, the energy storage system (ESS) with auxiliary frequency regulation based on droop control is proposed, and the engineering parameter and ESS′s power margin design method are given. In addition, a small signal model of the DG-ESS system is established to prove the stability of the system. Finally, the experimental platform of DG-ESS microgrid is built, and the results verify that the proposed control strategy effectively reduces the transient frequency fluctuation under the change of static or motor load.

Single-modal medical images contain limited disease-specific information. To analyze and diagnose patients, clinicians often need to integrate multiple modal images. However, due to limited medical resources and treatment time, it may be difficult to obtain multi-modal images. Cross-modal image reconstruction can generate medical images for clinical needs, thus assisting clinicians in accurately diagnosing and treating diseases. Traditional cross-modal reconstruction techniques have been applied in some clinical scenarios, but the quality of the reconstructed images needs further improvement. Generative adversarial network (GAN) can recover high-quality and complete image data from low-quality or incomplete medical image data, maximally savings medical equipment resources and accelerating medical treatment speed. This article summarizes the applications of GAN technology in cross-modal image reconstruction across X-ray imaging, computed tomography imaging, magnetic resonance imaging, and positron emission tomography imaging, to provide reference for the development of more advanced cross-modal reconstruction techniques.

To reduce errors in sub-synchronous oscillation (SSO) modal identification and improve the accuracy and noise resistance of the traditional Prony algorithm, this paper focuses on SSOs caused by the integration of doubly fed induction generators (DFIGs) with series compensation into the grid. A novel SSO modal identification method based on the hippopotamus optimization–variational mode decomposition (HO-VMD) and singular value decomposition–regularized total least squares–Prony (SVD-RTLS-Prony) algorithms is proposed. First, the energy ratio function is used for real-time monitoring of the system to identify oscillation signals. Then, to address the limitations of the VMD algorithm, the HO algorithm’s excellent optimization capabilities were utilized to improve the VMD algorithm, leading to preliminary denoising. Finally, the SVD-RTLS-improved Prony algorithm was employed to further suppress noise interference and extract oscillation characteristics, allowing for the accurate identification of SSO modes. The performance of the proposed method was evaluated using theoretical and practical models on the Matlab and PSCAD simulation platforms. The results indicate that the algorithms effectively perform denoising and accurately identify the characteristics of SSO signals, confirming its effectiveness, accuracy, superiority, and robustness against interference.

During the fault period, a phase angle jump may occur at the stator or the point of common coupling, which will deteriorate the low-voltage ride-through (LVRT) characteristics of a doubly fed induction generator (DFIG). The existing LVRT studies focus on the impact of a voltage drop on DFIGs but often ignore that of a phase angle jump. The time-domain simulation is accurate in describing the response of a DFIG during the LVRT process, but it is time-consuming for a DFIG with the full-order model. In this paper, by using the voltage magnitude and phase angle of the stator or the point of common coupling as the inputs, and the state variables as the outputs, the transfer function of a DFIG is derived to analyze its response and find the LVRT measures against the voltage drop and, especially, the phase angle jump. Firstly, the differential-algebraic equations of the DFIG are linearized to propose their transfer function model. Secondly, considering its high-order characteristic, a model reduction method for the transfer function of the DFIG using the Schur decomposition is proposed, and the analytical expression of the output variables of the DFIG with the phase angle jump is derived by the inverse Laplace transformation to judge the necessity of the LVRT measures. Finally, the simulation results of the DFIG are provided to verify the accuracy of the transfer function model and its reduced-order form and validate the feasibility of the LVRT against the phase angle jump with the proposed models.

Fungal secondary metabolites (SMs) represent an invaluable source of therapeutic drugs. Genomics-based approaches to SM discovery have revealed a vast and largely untapped biosynthetic potential within fungal genomes. Here, we used the publicly available fungal genome sequences from the NCBI public database, as well as tools such as antiSMASH, BIG-SLiCE, etc., to analyze a total of 11,598 fungal genomes, identifying 293,926 biosynthetic gene clusters (BGCs), which were subsequently categorized into 26,825 gene cluster families (GCFs). It was discovered that only a tiny fraction, less than 1%, of these GCFs could be mapped to known natural products (NPs). Some GCFs that only contain a single BGC internally are crucial for the biodiversity of fungal biosynthesis. Evident patterns emerged from our analysis, revealing popular taxa as prominent sources of both actual and potential biosynthetic diversity. Our study also suggests that the genus rank distribution of GCF is generally consistent with NP diversity. It is noteworthy that genera Xylaria, Hypoxylon, Colletotrichum, Diaporthe, Nemania, and Calonectria appear to possess a higher potential for SM synthesis. In addition, 7213 BGCs match possible known compound structures, and homologous gene clusters of well-known drugs can be located in different genera, facilitating the development of derivatives that share structural similarity to these drugs and may potentially possess similar biological activity. Our study demonstrated the various types of fungi with mining potential, assisting researchers in prioritizing their research efforts and avoiding duplicate mining of known resources to further explore fungal NP producers.