Comparative analysis of psychiatric medications and their association with falls and fractures: A systematic review and network meta-analysis.

An association between psychiatric medications and falls and fractures in people taking them has been demonstrated, but which class or medication leads to the greatest risk of falls or fractures should be further investigated. The aim of this study was to compare and rank the magnitude of risk of falls and fractures due to different psychiatric medications. Eight databases were searched for this meta-analysis and evaluated using a frequency-based network meta-analysis. The results included a total of 28 papers with 14 medications from 5 major classes, involving 3,467,314 patients. The results showed that atypical antipsychotics were the class of medications with the highest risk of falls, and typical antipsychotics were the class of medications with the highest risk of resulting in fractures. Quetiapine ranked first in the category of 13 medications associated with risk of falls, and class Z drugs ranked first in the category of 6 medications associated with risk of fractures. The available evidence suggests that atypical antipsychotics and typical antipsychotics may be the drugs with the highest risk of falls and fractures, respectively. Quetiapine may be the medication with the highest risk of falls, and class Z drugs may be the medication with the highest risk of fractures.

Vertebral HU value and the pectoral muscle index based on chest CT can be used to opportunistically screen for osteoporosis.

BACKGROUND: Existing studies have shown that computed tomography (CT) attenuation and skeletal muscle tissue are strongly associated with osteoporosis; however, few studies have examined whether vertebral HU values and the pectoral muscle index (PMI) measured at the level of the 4th thoracic vertebra (T4) are strongly associated with bone mineral density (BMD). In this study, we demonstrate that vertebral HU values and the PMI based on chest CT can be used to opportunistically screen for osteoporosis and reduce fracture risk through prompt treatment. METHODS: We retrospectively evaluated 1000 patients who underwent chest CT and DXA scans from August 2020-2022. The T4 HU value and PMI were obtained using manual chest CT measurements. The participants were classified into normal, osteopenia, and osteoporosis groups based on the results of dual-energy X-ray (DXA) absorptiometry. We compared the clinical baseline data, T4 HU value, and PMI between the three groups of patients and analyzed the correlation between the T4 HU value, PMI, and BMD to further evaluate the diagnostic efficacy of the T4 HU value and PMI for patients with low BMD and osteoporosis. RESULTS: The study ultimately enrolled 469 participants. The T4 HU value and PMI had a high screening capacity for both low BMD and osteoporosis. The combined diagnostic model-incorporating sex, age, BMI, T4 HU value, and PMI-demonstrated the best diagnostic efficacy, with areas under the receiver operating characteristic curve (AUC) of 0.887 and 0.892 for identifying low BMD and osteoporosis, respectively. CONCLUSIONS: The measurement of T4 HU value and PMI on chest CT can be used as an opportunistic screening tool for osteoporosis with excellent diagnostic efficacy. This approach allows the early prevention of osteoporotic fractures via the timely screening of individuals at high risk of osteoporosis without requiring additional radiation.

Toenail and blood selenium mediated regulation of thyroid dysfunction through immune cells: a mediation Mendelian randomization analysis.

Purpose: Specific nutrients found in food, such as minerals, antioxidants, and macronutrients, have a significant impact on immune function and human health. However, there is currently limited research exploring the relationship between specific nutrients, immune system function, and thyroid dysfunction commonly observed in autoimmune thyroid diseases, which manifest predominantly as hyperthyroidism or hypothyroidism. Therefore, the objective of this study was to investigate the connections between dietary traits and thyroid dysfunction, as well as the potential mediating role of immune cells, using Mendelian randomization (MR) analysis. Methods: The two-step MR analysis used single-nucleotide polymorphisms as instruments, with a threshold of p < 5e-08 for nutrients and thyroid dysfunction, and p < 5e-06 for immune cells. Data from different GWAS databases and UK Biobank were combined to analyze 8 antioxidants and 7 minerals, while the data for 4 macronutrients came from a cohort of 235,000 individuals of European. The outcome data (hypothyroidism, N = 3340; hyperthyroidism, N = 1840; free thyroxin [FT4], N = 49,269; thyroid-stimulating hormone [TSH], N = 54,288) were source from the ThyroidOmics consortium. Immune trait data, including 731 immune phenotypes, were collected from the GWAS catalog. Results: The results revealed that nutrient changes, such as lycopene, toenail and blood selenium, and α-tocopherol, impacted the immune system. Immune cells also affected thyroid function, with cDC cells promoting hypothyroidism and median fluorescence intensity (MFI) phenotypes correlating strongly with FT4 levels. Toenail and blood selenium reduce the relative cell counts (RCC) phenotypes of immune cells (CD62L- plasmacytoid DC %DC and transitional B cells %Lymphocyte), thereby diminishing its promoting effect on hypothyroidis. Furthermore, toenail and blood selenium mainly impacted phenotypes in three types of T cells (CD25 + ⁣ + CD8br, CD3 on CD45RA- CD4+, and CD45RA on Terminally Differentiated CD8br), reinforcing the negative regulation of FT4 levels. Conclusion: The role of immune cells as mediators in the relationship between nutrients and thyroid dysfunction highlights their potential as diagnostic or therapeutic markers. Toenail and blood selenium levels can indirectly impact hypothyroidism by influencing the RCC levels of two types of immune cells, and can indirectly affect FT4 levels by influencing three types of T cells.

Anterior Shoulder Stabilization Using Single Needle-Assisted Outside-In Remplissage Technique and Bankart Repair.

Arthroscopic repair of Bankart injury is the first choice for the treatment of anterior shoulder instability. How to avoid recurring shoulder joint dislocation is a challenge, especially when combined with Hill-Sachs lesions. The arthroscopy technology allows for broader vision and less surgical trauma but is limited by a smaller operating space. At present, extensive descriptions about the surgical procedure of arthroscopic Bankart repair have been published. In this Technical Note, we describe the use of remplissage filling with Hill-Sachs lesion combined with Bankart repair to further improve the surgical accuracy and clinical efficacy. In particular, the application of single needle-assisted outside-in remplissage technique and Bankart repair is introduced in detail.

Fully Floatable Mortise-and-Tenon Architecture for Synergistically Photo/Sono-Driven Evaporation Desalination and Plastic-Enabled Value-Added Co-Conversion of H2O and CO2.

Establishing an advanced ecosystem incorporating freshwater harvesting, plastic utilization, and clean fuel acquisition is profoundly significant. However, low-efficiency evaporation, single energy utilization, and catalyst leakage severely hinder sustainable development. Herein, a nanofiber-based mortise-and-tenon structural Janus aerogel (MTSJA) is strategically designed in the first attempt and supports Z-scheme catalysts. By harnessing of the upper hydrophilic layer with hydrophilic channels embedding into the hydrophobic bottom layer to achieve tailoring bottom wettability states. MTSJA is capable of a fully-floating function for lower heat loss, water supply, and high-efficiency solar-to-vapor conversion. Benefiting from the ultrasonic cavitation effect and high sensitivity of materials to mechanical forces, this is also the first demonstration of synergistic solar and ultrasound fields to power simultaneous evaporation desalination and waste plastics as reusable substrates generating fuel energy. The system enables persistent desalination with an exceptional evaporation rate of 3.1 kg m-2 h-1 and 82.3% efficiency (21 wt.% NaCl solution and 1 sun), and realizes H2, CO, and CH4 yields with 16.1, 9.5, and 3 µmol h-1 g-1, respectively. This strategy holds great potential for desalination and plastics value-added transformation toward clean energy and carbon neutrality.

Increased risk of fetal left-right asymmetry disorders associated with maternal SARS-CoV-2 infection during the first trimester.

Our center has observed a substantial increase in the detection rate of fetal left-right(LR) asymmetry disorders between March and May 2023. This finding has raised concerns because these pregnant women experienced the peak outbreak of SARS-CoV-2 in China during their first trimester. To explore the relationship between maternal SARS-CoV-2 infection and fetal LR asymmetry disorders. A retrospective collection of clinical and ultrasound data diagnosed as fetal LR asymmetry disorders was conducted from January 2018 to December 2023. The case-control study involved fetuses with LR asymmetry disorders and normal fetuses in a 1:1 ratio. We evaluated and compared the clinical and fetal ultrasound findings in pregnant women with SARS-CoV-2 infection and pregnant women without infection. The Student t-test was utilized to compare continuous variables, while the chi-squared test was employed for univariable analyses. The incidence rate of LR asymmetry disorders from 2018 to 2023 was as follows: 0.17‰, 0.63‰, 0.61‰, 0.57‰, 0.59‰, and 3.24‰, respectively. A total of 30 fetuses with LR asymmetry disorders and 30 normal fetuses were included. This case-control study found that SARS-CoV-2 infection (96.67% vs 3.33%, P = .026) and infection during the first trimester (96.55% vs 3.45%, P = .008) were identified as risk factors. The odds ratio values were 10.545 (95% CI 1.227, 90.662) and 13.067 (95% CI 1.467, 116.419) respectively. In cases of SARS-CoV-2 infection in the first trimester, the majority of infections (88.1%, 37/42) occurred between 5 and 6 weeks of gestation. We found that 43.7% (66/151) of fetuses with LR asymmetry disorder had associated malformations, 90.9% (60/66) exhibited cardiac malformations. SARS-CoV-2 infection during the first trimester significantly increases the risk of fetal LR asymmetry disorders, particularly when the infection occurs between 5 and 6 gestation weeks. The most common associated malformation is heart malformation.

Physeal-Sparing, All-Inside Anterior Cruciate Ligament Reconstruction Using Quadrupled Semitendinosus Autograft and Suture Tape Augmentation for Skeletally Immature Patients.

The anterior cruciate ligament (ACL) is the primary soft-tissue structure for anterior stabilization of the knee and is one of the most frequently injured structures. The incidence of ACL injuries in children and adolescents ranges from 92 to 151 per 100,000 person-years. The choice of surgical treatment for this population group is controversial, with a widespread concern that adult reconstruction techniques may damage the epiphyseal plate, compromise growth, or cause deformity. In this article, we describe a physeal-sparing, all-inside ACL reconstruction technique for skeletally immature patients. This technique is supported by retrograde drilling of the femoral tunnel and retrograde drilling of the tibial tunnel, both of which are able to avoid the epiphyseal growth line. Fixation of the quadrupled semitendinosus autograft and suture tape augmentation are achieved by soft-tissue buttons on the femur and tibia. The surgical details of this reproducible reconstruction technique are elaborated.

Novel Synergistic Probiotic Intervention: Transcriptomic and Metabolomic Analysis Reveals Ameliorative Effects on Immunity, Gut Barrier, and Metabolism of Mice during Salmonella typhimurium Infection.

Salmonella typhimurium (S. typhimurium), a prevalent cause of foodborne infection, induces significant changes in the host transcriptome and metabolome. The lack of therapeutics with minimal or no side effects prompts the scientific community to explore alternative therapies. This study investigates the therapeutic potential of a probiotic mixture comprising Lactobacillus acidophilus (L. acidophilus 1.3251) and Lactobacillus plantarum (L. plantarum 9513) against S. typhimurium, utilizing transcriptome and metabolomic analyses, a novel approach that has not been previously documented. Twenty-four SPF-BALB/c mice were divided into four groups: control negative group (CNG); positive control group (CPG); probiotic-supplemented non-challenged group (LAPG); and probiotic-supplemented Salmonella-challenged group (LAPST). An RNA-sequencing analysis of small intestinal (ileum) tissue revealed 2907 upregulated and 394 downregulated DEGs in the LAPST vs. CPG group. A functional analysis of DEGs highlighted their significantly altered gene ontology (GO) terms related to metabolism, gut integrity, cellular development, and immunity (p ≤ 0.05). The KEGG analysis showed that differentially expressed genes (DEGs) in the LAPST group were primarily involved in pathways related to gut integrity, immunity, and metabolism, such as MAPK, PI3K-Akt, AMPK, the tryptophan metabolism, the glycine, serine, and threonine metabolism, ECM-receptor interaction, and others. Additionally, the fecal metabolic analysis identified 1215 upregulated and 305 downregulated metabolites in the LAPST vs. CPG group, implying their involvement in KEGG pathways including bile secretion, propanoate metabolism, arginine and proline metabolism, amino acid biosynthesis, and protein digestion and absorption, which are vital for maintaining barrier integrity, immunity, and metabolism. In conclusion, these findings suggest that the administration of a probiotic mixture improves immunity, maintains gut homeostasis and barrier integrity, and enhances metabolism in Salmonella infection.

Screening and Diagnosis of Rare Thalassemia Variants: Is Third-Generation Sequencing Enough?

CONTEXT.­: Rare thalassemia subtypes are often undiagnosed because conventional testing methods can only identify 23 common types of α- and ß-thalassemia. OBJECTIVE.­: To assess a comprehensive approach for the screening and diagnosis of rare thalassemia. DESIGN.­: The study cohort included 72 individuals with suspected rare thalassemia variants. Screening was conducted by next-generation sequencing (NGS) combined with third-generation sequencing (TGS) and chromosomal microarray analysis (CMA)/copy number variation sequencing. RESULTS.­: Of the 72 individuals with suspected rare thalassemia, 49 had rare α- or ß-gene variants. NGS combined with gap polymerase chain reaction detected a total of 42 cases, resulting in a positive detection rate of 58.3%. Additionally, 4 α-globin genetic deletions were identified by TGS, which increased the variant detection rate by 5.6%. Two samples with a microdeletion of chromosome 16 or 11 were detected by CMA, which increased the detection rate by 2.8%. For one sample, reanalysis of the NGS and TGS data confirmed the presence of the ß41-42/ßN and ßN/ßN mosaic. The HBB:c.315 + 2delT mutation was initially reported in Guangdong Province, China. Two HBB gene mutations (HBB:c.315 + 5G>C and HBB:c.295G>A) and 4 rare HBA gene deletions (-11.1, -α27.6, -α2.4, and -α21.9) were initially identified in the Zhonshan region. The hematologic phenotypes of all rare cases in this study were clarified. CONCLUSIONS.­: Rare thalassemia variants are more common than previously thought. Despite advancements in TGS, there is still no foolproof method for detection of all types of thalassemia. Thus, a comprehensive approach is necessary for accurate screening and diagnosis of rare thalassemia variants.

Non-enzymatic Detection of Uric Acid in Serum and Urine by Fluorescent and Visual Dual-Mode Sensor Based on 3-aminophenylboric Acid Functionalized Carbon Dots.

Herein, we developed a sophisticated dual-mode sensor that utilized 3-aminophenylboric acid functionalized carbon dots (APBA-CDs) to accurately detect uric acid (UA). Our innovative process involved synthesizing APBA-CDs that emitted at 369 nm using a one-step hydrothermal method with 3-aminophenylboric acid and L-glutamine as precursors, ethanol and deionized water as solvents. Once UA was introduced to the APBA-CDs, the fluorescence of the system became visibly quenched. The results of Zeta potential, Fourier transformed infrared (FTIR) spectra, fluorescence lifetime, and other characteristics were analyzed to determine that the reaction mechanism was static quenching. This meant that after UA was mixed with APBA-CDs, it combined with the boric acid function on the surface to form complexes, resulting in a decrease in fluorescence intensity and a blue shift in the absorption peak at about 295 nm in the Ultraviolet-visible (UV-vis) absorption spectra. We were pleased to report that we have successfully used the dual-reading platform to accurately detect UA in serum and human urine. It provided a superior quantitative and visual analysis of UA without the involvement of enzymes. We firmly believe that our innovative dual-mode sensor has immense potential in the fields of biosensing and health monitoring.

PLMSearch: Protein language model powers accurate and fast sequence search for remote homology.

Homologous protein search is one of the most commonly used methods for protein annotation and analysis. Compared to structure search, detecting distant evolutionary relationships from sequences alone remains challenging. Here we propose PLMSearch (Protein Language Model), a homologous protein search method with only sequences as input. PLMSearch uses deep representations from a pre-trained protein language model and trains the similarity prediction model with a large number of real structure similarity. This enables PLMSearch to capture the remote homology information concealed behind the sequences. Extensive experimental results show that PLMSearch can search millions of query-target protein pairs in seconds like MMseqs2 while increasing the sensitivity by more than threefold, and is comparable to state-of-the-art structure search methods. In particular, unlike traditional sequence search methods, PLMSearch can recall most remote homology pairs with dissimilar sequences but similar structures. PLMSearch is freely available at https://dmiip.sjtu.edu.cn/PLMSearch .

Optimization of ultrasound-assisted extraction of Imperata cylindrica polysaccharides and evaluation of its anti-oxidant and amelioration of uric acid stimulated cell apoptosis.

An efficient, cost-effective and environmentally friendly ultrasound-assisted hot water method for Imperata cylindrica polysaccharide (ICPs) extraction was developed. According to the response surface results, the optimal ultrasonic time was 85 min, ultrasonic power was 192.75 W, temperature was 90.74 °C, liquid-solid ratio was 26.1, and polysaccharide yield was 28.50 %. The polysaccharide mainly consisted of arabinose (Ara), galactose (Gal), and glucose (Glc), with a molecular weight of 62.3 kDa. Ultrasound-assisted extraction of Imperata cylindrica polysaccharide (UICP) exhibited stronger anti-oxidant activity and ability to ameliorate cellular damage due to uric acid stimulation compared with traditional hot water extraction of Imperata cylindrica polysaccharide (ICPC-b). It also exhibited higher thermal stability, indicating its potential value for applications in the food industry.

ReHoGCNES-MDA: prediction of miRNA-disease associations using homogenous graph convolutional networks based on regular graph with random edge sampler.

Numerous investigations increasingly indicate the significance of microRNA (miRNA) in human diseases. Hence, unearthing associations between miRNA and diseases can contribute to precise diagnosis and efficacious remediation of medical conditions. The detection of miRNA-disease linkages via computational techniques utilizing biological information has emerged as a cost-effective and highly efficient approach. Here, we introduced a computational framework named ReHoGCNES, designed for prospective miRNA-disease association prediction (ReHoGCNES-MDA). This method constructs homogenous graph convolutional network with regular graph structure (ReHoGCN) encompassing disease similarity network, miRNA similarity network and known MDA network and then was tested on four experimental tasks. A random edge sampler strategy was utilized to expedite processes and diminish training complexity. Experimental results demonstrate that the proposed ReHoGCNES-MDA method outperforms both homogenous graph convolutional network and heterogeneous graph convolutional network with non-regular graph structure in all four tasks, which implicitly reveals steadily degree distribution of a graph does play an important role in enhancement of model performance. Besides, ReHoGCNES-MDA is superior to several machine learning algorithms and state-of-the-art methods on the MDA prediction. Furthermore, three case studies were conducted to further demonstrate the predictive ability of ReHoGCNES. Consequently, 93.3% (breast neoplasms), 90% (prostate neoplasms) and 93.3% (prostate neoplasms) of the top 30 forecasted miRNAs were validated by public databases. Hence, ReHoGCNES-MDA might serve as a dependable and beneficial model for predicting possible MDAs.

First-in-human phase I study of BEBT-109 in previously treated EGFR exon 20 insertion-mutated advanced non-small cell lung cancer.

BACKGROUND: BEBT-109 is an oral pan-mutant-selective inhibitor of epidermal growth factor receptor (EGFR) that demonstrated promising antitumor potency in preclinical models. METHODS: This first-in-human study was a single-arm, open-label, two-stage study. Phase Ia dose-escalation study evaluated the safety and pharmacokinetics of BEBT-109 in 11 patients with EGFR T790M-mutated advanced non-small cell lung cancer (aNSCLC). Phase Ib dose-expansion study evaluated the safety and efficacy of BEBT-109 in 18 patients with EGFR exon 20 insertion (ex20ins)-mutated treatment-refractory aNSCLC. The primary outcomes were adverse events and antitumor activity. Clinical trial registration number CTR20192575. FINDINGS: The phase Ia study demonstrated no dose-limiting toxicity, no observation of the maximum tolerated dose, and no new safety signals with BEBT-109 in the dose range of 20-180 mg/d, suggesting that BEBT-109 had an acceptable safety profile among patients with EGFR T790M-mutated aNSCLC. Plasma pharmacokinetics of BEBT-109 showed a dose-proportional increase in the area under the curve and maximal concentration, with no significant drug accumulation. The dose-expansion study demonstrated that BEBT-109 treatment was tolerable across the three dose levels. The three most common treatment-related adverse events were diarrhea (100%; 22.2% ≥Grade 3), rash (66.7%; 5.6% ≥Grade 3), and anemia (61.1%; 0% ≥Grade 3). The objective response rate was 44.4% (8 of 18). Median progression-free survival was 8.0 months (95% confidence intervals, 1.33-14.67). CONCLUSION: Preliminary findings showed that BEBT-109 had an acceptable safety profile and favorable antitumor activity in patients with refractory EGFR ex20ins-mutated aNSCLC. FUNDING: National Natural Science Foundation of China.

Bioactivities and Action Mechanisms of Ellipticine Derivatives Reported Prior to 2023.

Currently, natural products are one of the priceless options for finding novel chemical pharmaceutical entities. Ellipticine is a naturally occurring alkaloid isolated from the leaves of Ochrosia elliptica Labill. Ellipticine and its derivatives are characterized by multiple biological activities. The purpose of this review was to provide a critical and systematic assessment of ellipticine and its derivatives as bioactive molecules over the last 60 years. Publications focused mainly on the total synthesis of alkaloids of this type without any evaluation of bioactivity have been excluded. We have reviewed papers dealing with the synthesis, bioactivity evaluation and mechanism of action of ellipticine and its derivatives. It was found that ellipticine and its derivatives showed cytotoxicity, antimicrobial ability, and anti-inflammatory activity, among which cytotoxicity toward cancer cell lines was the most investigated aspect. The inhibition of DNA topoisomerase II was the most relevant mechanism for cytotoxicity. The PI3K/AKT pathway, p53 pathway, and MAPK pathway were also closely related to the antiproliferative ability of these compounds. In addition, the structure-activity relationship was deduced, and future prospects were outlined. We are confident that these findings will lay a scientific foundation for ellipticine-based drug development, especially for anticancer agents.

Electrothermally controlled origami fabricated by 4D printing of continuous fiber-reinforced composites.

Active origami capable of precise deployment control, enabling on-demand modulation of its properties, is highly desirable in multi-scenario and multi-task applications. While 4D printing with shape memory composites holds great promise to realize such active origami, it still faces challenges such as low load-bearing capacity and limited transformable states. Here, we report a fabrication-design-actuation method of precisely controlled electrothermal origami with excellent mechanical performance and spatiotemporal controllability, utilizing 4D printing of continuous fiber-reinforced composites. The incorporation of continuous carbon fibers empowers electrothermal origami with a controllable actuation process via Joule heating, increased actuation force through improved heat conduction, and enhanced mechanical properties as a result of reinforcement. By modeling the multi-physical and highly nonlinear deploying process, we attain precise control over the active origami, allowing it to be reconfigured and locked into any desired configuration by manipulating activation parameters. Furthermore, we showcase the versatility of electrothermal origami by constructing reconfigurable robots, customizable architected materials, and programmable wings, which broadens the practical engineering applications of origami.

CloudProteoAnalyzer: scalable processing of big data from proteomics using cloud computing.

Summary: Shotgun proteomics is widely used in many system biology studies to determine the global protein expression profiles of tissues, cultures, and microbiomes. Many non-distributed computer algorithms have been developed for users to process proteomics data on their local computers. However, the amount of data acquired in a typical proteomics study has grown rapidly in recent years, owing to the increasing throughput of mass spectrometry and the expanding scale of study designs. This presents a big data challenge for researchers to process proteomics data in a timely manner. To overcome this challenge, we developed a cloud-based parallel computing application to offer end-to-end proteomics data analysis software as a service (SaaS). A web interface was provided to users to upload mass spectrometry-based proteomics data, configure parameters, submit jobs, and monitor job status. The data processing was distributed across multiple nodes in a supercomputer to achieve scalability for large datasets. Our study demonstrated SaaS for proteomics as a viable solution for the community to scale up the data processing using cloud computing. Availability and implementation: This application is available online at https://sipros.oscer.ou.edu/ or https://sipros.unt.edu for free use. The source code is available at https://github.com/Biocomputing-Research-Group/CloudProteoAnalyzer under the GPL version 3.0 license.

scDOT: enhancing single-cell RNA-Seq data annotation and uncovering novel cell types through multi-reference integration.

The proliferation of single-cell RNA-seq data has greatly enhanced our ability to comprehend the intricate nature of diverse tissues. However, accurately annotating cell types in such data, especially when handling multiple reference datasets and identifying novel cell types, remains a significant challenge. To address these issues, we introduce Single Cell annotation based on Distance metric learning and Optimal Transport (scDOT), an innovative cell-type annotation method adept at integrating multiple reference datasets and uncovering previously unseen cell types. scDOT introduces two key innovations. First, by incorporating distance metric learning and optimal transport, it presents a novel optimization framework. This framework effectively learns the predictive power of each reference dataset for new query data and simultaneously establishes a probabilistic mapping between cells in the query data and reference-defined cell types. Secondly, scDOT develops an interpretable scoring system based on the acquired probabilistic mapping, enabling the precise identification of previously unseen cell types within the data. To rigorously assess scDOT's capabilities, we systematically evaluate its performance using two diverse collections of benchmark datasets encompassing various tissues, sequencing technologies and diverse cell types. Our experimental results consistently affirm the superior performance of scDOT in cell-type annotation and the identification of previously unseen cell types. These advancements provide researchers with a potent tool for precise cell-type annotation, ultimately enriching our understanding of complex biological tissues.