Adaptive Weighted Data Fusion for Line Structured Light and Photometric Stereo Measurement System.

Line structured light (LSL) measurement systems can obtain high accuracy profiles, but the overall clarity relies greatly on the sampling interval of the scanning process. Photometric stereo (PS), on the other hand, is sensitive to tiny features but has poor geometrical accuracy. Cooperative measurement with these two methods is an effective way to ensure precision and clarity results. In this paper, an LSL-PS cooperative measurement system is brought out. The calibration methods used in the LSL and PS measurement system are given. Then, a data fusion algorithm with adaptive weights is proposed, where an error function that contains the 3D point cloud matching error and normal vector error is established. The weights, which are based on the angles of adjacent normal vectors, are also added to the error function. Afterward, the fusion results can be obtained by solving linear equations. From the experimental results, it can be seen that the proposed method has the advantages of both the LSL and PS methods. The 3D reconstruction results have the merits of high accuracy and high clarity.

Clinical efficacy of magnetic vibration magnetoelectric therapy in the treatment of chronic prostatitischronic pelvic pain syndrome.

BACKGROUND: The prominent symptoms of chronic pelvic pain syndrome (CPPS) are urogenital pain, lower urinary tract symptoms, psychological problems, and sexual dysfunction. Traditional pharmacological treatments have poor efficacy and more untoward reaction and complications. Magnetic vibration magnetoelectric therapy is a non-invasive form of physiotherapy. Nevertheless, its effectiveness in improving urinary discomfort and relieving pain in patients requires further exploration. AIM: To investigate the clinical efficacy of the magnetic vibration magnetoelectric therapy instrument in the treatment of chronic prostatitis (CP)/ CPPS. METHODS: Seventy patients with CP/CPPS were collected from the outpatient clinic and ward of the Department of Male Medicine, Jiangsu Province Hospital of Traditional Chinese Medicine, and were treated with magnetic vibration magnetoelectric therapy once a day for a period of 14 d. National Institutes of health-chronic prostatitis symptom index (NIH-CPSI), international index of erectile function 5 (IIEF-5), premature ejaculation diagnostic tool (PEDT), generalized anxiety disorder (GAD), patient health questionnaire, the pain catastrophizing scale (PCS) and traditional Chinese medicine syndrome (TCMS) scores were performed before and after treatment. RESULTS: The total effective rate of treatment was 58.5%, and the total NIH-CPSI score, pain symptoms, voiding symptoms, quality of life, IIEF-5, PEDT, GAD, PCS and TCMS scores all decreased significantly (P < 0.05). CONCLUSION: Magnetic vibration magnetotherapy is effective in improving urinary discomfort, relieving pain, improving quality of life, improving sexual dysfunction and relieving negative emotions such as anxiety in patients with CP/CPPS.

Observation of the Transition from Triple Bonds to Single Bonds between Ru-Ge Bonding in RuGeO(CO)n- (n = 3-5).

This work reports the observation and characterization of heterobinuclear transition-metal main-group metal oxide carbonyl complex anions, RuGeO(CO)n- (n = 3-5), by combining mass-selected photoelectron velocity map imaging spectroscopy and quantum chemistry calculations. The experimentally determined vertical electron detachment energy of RuGeO(CO)3- surpasses those of RuGeO(CO)4- and RuGeO(CO)5-, which is attributed to distinctive bonding features. RuGeO(CO)3- manifests one covalent σ and two Ru-to-Ge dative π bonds, contrasting with the sole covalent σ bond present in RuGeO(CO)4- and RuGeO(CO)5-. Unpaired spin density distribution analysis reveals a 17-electron configuration at the Ru center in RuGeO(CO)3- and an 18-electron configuration in RuGeO(CO)4- and RuGeO(CO)5-. This work closes a gap in the quantitative physicochemical characterization of heteronuclear oxide carbonyl complexes, enhancing our insights into catalytic processes of CO/GeO on the metal surface at the molecular level.

Association of PD-L1 expression and clinical outcomes in ROS1 - rearranged advanced non-small cell lung cancer treated with crizotinib.

Background: Programmed cell death ligand 1 (PD-L1) is more readily expressed in ROS proto-oncogene 1 (ROS1) rearranged non-small cell lung cancer (NSCLC) compared to NSCLC cases lacking driver gene mutations. Prior research has established a link between PD-L1 expression and reduced effectiveness of EGFR or ALK inhibitors in EGFR or ALK-positive NSCLC. Nonetheless, the relationship between initial PD-L1 levels and the clinical impact of first-line crizotinib therapy in ROS1-rearranged NSCLC is still uncertain. Methods: From January 2016 to December 2021, a total of 246 patients with ROS1 positive tumors were collected. Out of these, 82 patients with advanced ROS1-rearranged NSCLC, who were treated with crizotinib as their initial therapy, were selected for the study. The study aimed primarily to evaluate the objective response rate (ORR) and progression-free survival (PFS), and secondarily to assess disease control rate (DCR) and overall survival (OS). Results: Of the 82 advanced ROS1-rearranged NSCLC patients, 38 exhibited PD-L1 positivity, subdivided into 11 with high and 27 with low expression levels, while the remaining 44 showed no PD-L1 expression. The ORR for all included patients was 80.5%. No statistically significant variance in ORR was observed among ROS1-rearranged NSCLC patients across differing PD-L1 expression statuses. However, there was a statistically significant difference in DCR between PD-L1 negative group (100%) and high expression group (90.9%) (p=0.04). The median PFS spanned 26.4 months for the PD-L1 negative group, 16.6 for the low expression group, and 13.7 for the high expression group (p=0.001). Additionally, a notable statistical disparity was also observed in median PFS between the PD-L1 negative and positive groups (p=0.02). For the entire study population, the median OS was 53.0 months (95% CI 43.8 - 62.2). In the PD-L1-negative group, the median OS reached 57.2 months, compared to 53.0 months in the PD-L1-positive group, a difference lacking statistical significance (p=0.43). Conclusions: Our results suggest that for ROS1-positive NSCLC patients receiving crizotinib as first-line therapy, PD-L1 expression may serve as a negative prognostic marker for PFS rather than OS.

Multichannel focused higher-order Poincaré sphere beam generation based on a dielectric geometric metasurface.

Focused vector beams (VBs) are important topic in the areas of light field manipulation. Geometric metasurfaces provide a convenient platform to facilitate the generation of focused VBs. In this study, we propose a dielectric geometric metasurface to generate multichannel focused higher-order Poincaré sphere (HOP) beams. With identical meta-atoms of half-wave plate, the metasurface comprises two sub-metasurfaces, and each of them includes two sets of rings related to Fresnel zones. For meta-atoms on each set of rings, the hyperbolic geometric phase profile is configured so that the mirror-symmetrical position-flip of the off-axis focal point is enabled under the chirality switch of the illuminating circular polarization. With the design of helical geometric phase profiles for the two sets of rings, a sub-metasurface generate two HOP beams at the symmetrical two focal points. The performance of the two sub-metasurfaces enables the metasurface with four sets of rings to generate the array of four HOP beams. The proposed method was validated by theoretical analyses, numerical simulation and experimental conduction. This research would be significant in miniaturizing and integrating optical systems involving applications of VB generations and applications.

Efficient and robust phase unwrapping method based on SFNet.

Phase unwrapping is a crucial step in obtaining the final physical information in the field of optical metrology. Although good at dealing with phase with discontinuity and noise, most deep learning-based spatial phase unwrapping methods suffer from the complex model and unsatisfactory performance, partially due to simple noise type for training datasets and limited interpretability. This paper proposes a highly efficient and robust spatial phase unwrapping method based on an improved SegFormer network, SFNet. The SFNet structure uses a hierarchical encoder without positional encoding and a decoder based on a lightweight fully connected multilayer perceptron. The proposed method utilizes the self-attention mechanism of the Transformer to better capture the global relationship of phase changes and reduce errors in the phase unwrapping process. It has a lower parameter count, speeding up the phase unwrapping. The network is trained on a simulated dataset containing various types of noise and phase discontinuity. This paper compares the proposed method with several state-of-the-art deep learning-based and traditional methods in terms of important evaluation indices, such as RMSE and PFS, highlighting its structural stability, robustness to noise, and generalization.

An Improved Dyna-Q Algorithm Inspired by the Forward Prediction Mechanism in the Rat Brain for Mobile Robot Path Planning.

The traditional Model-Based Reinforcement Learning (MBRL) algorithm has high computational cost, poor convergence, and poor performance in robot spatial cognition and navigation tasks, and it cannot fully explain the ability of animals to quickly adapt to environmental changes and learn a variety of complex tasks. Studies have shown that vicarious trial and error (VTE) and the hippocampus forward prediction mechanism in rats and other mammals can be used as key components of action selection in MBRL to support "goal-oriented" behavior. Therefore, we propose an improved Dyna-Q algorithm inspired by the forward prediction mechanism of the hippocampus to solve the above problems and tackle the exploration-exploitation dilemma of Reinforcement Learning (RL). This algorithm alternately presents the potential path in the future for mobile robots and dynamically adjusts the sweep length according to the decision certainty, so as to determine action selection. We test the performance of the algorithm in a two-dimensional maze environment with static and dynamic obstacles, respectively. Compared with classic RL algorithms like State-Action-Reward-State-Action (SARSA) and Dyna-Q, the algorithm can speed up spatial cognition and improve the global search ability of path planning. In addition, our method reflects key features of how the brain organizes MBRL to effectively solve difficult tasks such as navigation, and it provides a new idea for spatial cognitive tasks from a biological perspective.

The impact of temperature, humidity and closing school on the mumps epidemic: a case study in the mainland of China.

BACKGROUND: To control resurging infectious diseases like mumps, it is necessary to resort to effective control and preventive measures. These measures include increasing vaccine coverage, providing the community with advice on how to reduce exposure, and closing schools. To justify such intervention, it is important to understand how well each of these measures helps to limit transmission. METHODS: In this paper, we propose a simple SEILR (susceptible-exposed-symptomatically infectious-asymptomatically infectious-recovered) model by using a novel transmission rate function to incorporate temperature, humidity, and closing school factors. This new transmission rate function allows us to verify the impact of each factor either separately or combined. Using reported mumps cases from 2004 to 2018 in the mainland of China, we perform data fitting and parameter estimation to evaluate the basic reproduction number  R 0 . As a wide range of one-dose measles, mumps, and rubella (MMR) vaccine programs in China started only in 2008, we use different vaccination proportions for the first Stage I period (from 2004 to 2008) and the second Stage II period (from 2009 to 2018). This allows us to verify the importance of higher vaccine coverage with a possible second dose of MMR vaccine. RESULTS: We find that the basic reproduction number  R 0  is generally between 1 and 3. We then use the Akaike Information Criteria to assess the extent to which each of the three factors contributed to the spread of mumps. The findings suggest that the impact of all three factors is substantial, with temperature having the most significant impact, followed by school opening and closing, and finally humidity. CONCLUSION: We conclude that the strategy of increasing vaccine coverage, changing micro-climate (temperature and humidity), and closing schools can greatly reduce mumps transmission.

scZAG: Integrating ZINB-Based Autoencoder with Adaptive Data Augmentation Graph Contrastive Learning for scRNA-seq Clustering.

Single-cell RNA sequencing (scRNA-seq) is widely used to interpret cellular states, detect cell subpopulations, and study disease mechanisms. In scRNA-seq data analysis, cell clustering is a key step that can identify cell types. However, scRNA-seq data are characterized by high dimensionality and significant sparsity, presenting considerable challenges for clustering. In the high-dimensional gene expression space, cells may form complex topological structures. Many conventional scRNA-seq data analysis methods focus on identifying cell subgroups rather than exploring these potential high-dimensional structures in detail. Although some methods have begun to consider the topological structures within the data, many still overlook the continuity and complex topology present in single-cell data. We propose a deep learning framework that begins by employing a zero-inflated negative binomial (ZINB) model to denoise the highly sparse and over-dispersed scRNA-seq data. Next, scZAG uses an adaptive graph contrastive representation learning approach that combines approximate personalized propagation of neural predictions graph convolution (APPNPGCN) with graph contrastive learning methods. By using APPNPGCN as the encoder for graph contrastive learning, we ensure that each cell's representation reflects not only its own features but also its position in the graph and its relationships with other cells. Graph contrastive learning exploits the relationships between nodes to capture the similarity among cells, better representing the data's underlying continuity and complex topology. Finally, the learned low-dimensional latent representations are clustered using Kullback-Leibler divergence. We validated the superior clustering performance of scZAG on 10 common scRNA-seq datasets in comparison to existing state-of-the-art clustering methods.

CPPLS-MLP: a method for constructing cell-cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data.

In the growth and development of multicellular organisms, the immune processes of the immune system and the maintenance of the organism's internal environment, cell communication plays a crucial role. It exerts a significant influence on regulating internal cellular states such as gene expression and cell functionality. Currently, the mainstream methods for studying intercellular communication are focused on exploring the ligand-receptor-transcription factor and ligand-receptor-subunit scales. However, there is relatively limited research on the association between intercellular communication and highly variable genes (HVGs). As some HVGs are closely related to cell communication, accurately identifying these HVGs can enhance the accuracy of constructing cell communication networks. The rapid development of single-cell sequencing (scRNA-seq) and spatial transcriptomics technologies provides a data foundation for exploring the relationship between intercellular communication and HVGs. Therefore, we propose CPPLS-MLP, which can identify HVGs closely related to intercellular communication and further analyze the impact of Multiple Input Multiple Output cellular communication on the differential expression of these HVGs. By comparing with the commonly used method CCPLS for constructing intercellular communication networks, we validated the superior performance of our method in identifying cell-type-specific HVGs and effectively analyzing the influence of neighboring cell types on HVG expression regulation. Source codes for the CPPLS_MLP R, python packages and the related scripts are available at 'CPPLS_MLP Github [https://github.com/wuzhenao/CPPLS-MLP]'.

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues.

The heterogeneity of tumors poses a challenge for understanding cell interactions and constructing complex ecosystems within cancer tissues. Current research strategies integrate spatial transcriptomics (ST) and single-cell sequencing (scRNA-seq) data to thoroughly analyze this intricate system. However, traditional deep learning methods using scRNA-seq data tend to filter differentially expressed genes through statistical methods. In the context of cancer tissues, where cancer cells exhibit significant differences in gene expression compared to normal cells, this heterogeneity renders traditional analysis methods incapable of accurately capturing differences between cell types. Therefore, we propose a graph-based deep learning method, GTADC, which utilizes Silhouette scores to precisely capture genes with significant expression differences within each cell type, enhancing the accuracy of gene selection. Compared to traditional methods, GTADC not only considers the expression similarity of genes within their respective clusters but also comprehensively leverages information from the overall clustering structure. The introduction of graph structure effectively captures spatial relationships and topological structures between the two types of data, enabling GTADC to more accurately and comprehensively resolve the spatial composition of different cell types within tissues. This refinement allows GTADC to intricately reconstruct the cellular spatial composition, offering a precise solution for inferring cell spatial composition. This method allows for early detection of potential cancer cell regions within tissues, assessing their quantity and spatial information in cell populations. We aim to achieve a preliminary estimation of cancer occurrence and development, contributing to a deeper understanding of early-stage cancer and providing potential support for early cancer diagnosis.

eCRUIS captures RNA-protein interaction in vitro and in vivo.

As an information bridge between DNA and protein, RNA regulates cellular processes and gene expression in various ways. From its synthesis to degradation, RNA is associated with a range of RNA-binding proteins. Therefore, it is necessary to develop innovative methods to study the interaction between RNA and proteins. Previously, we developed an RNA-centric method, called CRISPR-based RNA-United Interacting System (CRUIS), to capture RNA-protein interaction in cells. On this basis, here we develop an enhanced CRUIS (eCRUIS) by combining the power of dCas13d and the engineered promiscuous ligase TurboID. The current version allows us to rapidly label RNA-binding proteins on the target RNA within 30 minutes, potentially for in vivo use. By introducing bait-assay with exogenous RNA, we confirm that eCRUIS can effectively label RNA-binding proteins on bait RNA in a short time. eCRUIS provides a broader range of in vitro and in vivo applications for studying RNA-protein interactions.

Description of a new species of the genus Woznessenskia from Xizang, China (Orthoptera: Gryllacrididae).

The gryllacridid genus Woznessenskia Gorochov, 2002 comprises 13 extant species from Asia, with 8 species reported from China and 5 species reported from Vietnam. A new species from Xizang, China, Woznessenskia lianhua sp. nov., is reported in this paper.

A new species of Svistella Gorochov, 1987 from Xizang, China (Orthoptera, Trigonidiidae, Trigonidiinae).

The genus Svistella Gorochov, 1987 includes 10 species from Asia, with nine documented in China. In this study, a new species, Svistellayayun He, sp. nov., is described from Xizang, China. Morphologically, it resembles S.rufonotata (Chopard, 1932) but can be distinguished by a smaller inner tympanum, dark-brown setae on the 5th segment of the maxillary palp, and a rounded apex on the ectoparamere. To validate our morphological inferences and support the description of S.yayunsp. nov. as a new species, we performed a PCA based on bioacoustics parameters and molecular analysis. All Svistella species documented in China are distinguished by integrating their songs and DNA barcoding.

Interplay Between Intracellular Transport Dynamics and Liquid‒Liquid Phase Separation.

Liquid‒liquid phase separation (LLPS) is a ubiquitous process in which proteins, RNA, and biomolecules assemble into membrane-less compartments, playing important roles in many biological functions and diseases. The current knowledge on the biophysical and biochemical principles of LLPS is largely from in vitro studies; however, the physiological environment in living cells is complex and not at equilibrium. The characteristics of intracellular dynamics and their roles in physiological LLPS remain to be resolved. Here, by using single-particle tracking of quantum dots and dynamic monitoring of the formation of stress granules (SGs) in single cells, the spatiotemporal dynamics of intracellular transport in cells undergoing LLPS are quantified. It is shown that intracellular diffusion and active transport are both reduced. Furthermore, the formation of SG droplets contributes to increased spatial heterogeneity within the cell. More importantly, the study demonstrated that the LLPS of SGs can be regulated by intracellular dynamics in two stages: the reduced intracellular diffusion promotes SG assembly and the microtubule-associated transport facilitates SG coalescences. The work on intracellular dynamics not only improves the understanding of the mechanism of physiology phase separations occurring in nonequilibrium environments but also reveals an interplay between intracellular dynamics and LLPS.

Excitation characteristics of circumferential SH guided waves in steel pipes generated by EMATs with few-cycle PPM.

Circumferential Shear Horizontal (CSH) guided waves provide an effective method for detecting defects like axial cracks and corrosion in pipes. Periodic Permanent Magnet Electromagnetic Acoustic Transducers (PPM EMATs) are typically used to generate CSH guided waves. However, there is an offset problem to which little attention has been paid. The offset problem refers to the offset of the center (position of maximum energy) of the operating region caused by the variation in the peak frequency of the spatial spectra of PPM with 2 or fewer cycles. Furthermore, the excitability of guided waves is one of the factors that needs to be considered when selecting the excitation parameters of EMATs, but there are still some studies that have not sufficiently addressed this issue. In this paper, the offset problem and the excitability of CSH guided waves were investigated. Firstly, by obtaining the operating regions corresponding to PPM with different cycles, the cause and influences of the offset problem were studied. The results show that the offset in the peak frequency of the spatial spectrum of PPM is the fundamental reason causing the offset problem, and it not only leads to incorrect prediction of the excitation efficiency of guided waves but also affects the selection of the excitation parameters of EMATs. Secondly, finite element simulations and experiments were performed to assess the influence of the excitability on the excitation efficiency of the CSH0 and CSH1 modes in pipes. By analyzing the simulation and experimental results of 2-cycle PPM, as well as the simulation results for PPM with 1 to 5 cycles, the impact of the excitability on the CSH1 mode was confirmed from two perspectives. The final conclusion indicates that an accurate prediction of the amplitudes of CSH guided waves with different modes is only possible through a comprehensively consideration of the operating region of EMAT and the excitability of guided waves.

Quarter-Wave Plate Metasurfaces for Generating Multi-Channel Vortex Beams.

Metasurfaces of quarter-wave plate (QWP) meta-atoms have exhibited high flexibility and versatile functionalities in the manipulation of light fields. However, the generation of multi-channel vortex beams with the QWP meta-atom metasurfaces presents a significant challenge. In this study, we propose dielectric metasurfaces composed of QWP meta-atoms to manipulate multi-channel vortex beams. QWP meta-atoms, systematically arranged in concentric circular rings, are designed to introduce the modulations via the propagation phase and geometric phase, leading to the generation of co- and cross-polarized vortex beams in distinct channels. Theoretical investigations and simulations are employed to analyze the modulation process, confirming the capability of QWP meta-atom metasurfaces for generating the multi-channel vortex beams. This study presents prospective advancements for the compact, integrated, and multifunctional nanophotonic platforms, which have potential applications in classical physics and quantum domains.

Efficacy of chemo-immunotherapy in metastatic BRAF-mutated lung cancer: a single-center retrospective data.

Background: The effectiveness of combining immune checkpoint inhibitors (ICIs) with chemotherapy in treating non-small cell lung cancers (NSCLCs) with BRAF mutations has not been sufficiently explored. Methods: We compiled data from 306 NSCLC patients with identified BRAF mutations. We looked at efficacy by assessing the objective response rate (ORR) and disease control rate (DCR), as well as survival through measuring progression-free survival (PFS) and overall survival (OS). Results: Out of the patient pool, 44 were treated with a regimen of immune-chemotherapy. Patients undergoing ICI in combination with chemotherapy had a median PFS of 4 months, and the median OS was recorded at 29 months. There was a notable increase in OS in patients receiving first-line treatment versus subsequent lines (29 vs 9.75 months, p=0.01); however, this was not the case with PFS (9 vs 4 months, p=0.46). The ORR for patients on ICIs was 36.3%. PFS and OS rates did not significantly differ between patients with the BRAF-V600E mutation and those with non-V600E mutations (p=0.75 and p=0.97, respectively). Additionally, we found a significant variation in PD-L1 expression between those who responded to treatment and those who didn't (p=0.04). Conclusion: Our findings indicate that chemo-immunotherapy as an initial treatment may lead to improved OS in patients with BRAF-mutated NSCLC when compared to its use in subsequent lines of therapy. Further studies are needed to validate these results and to delve deeper into how specific types of BRAF mutations and PD-L1 expression levels might predict a patient's response to treatments in NSCLC.

Efficacy of immune checkpoint inhibitors in advanced large cell neuroendocrine carcinoma of the lung: A single­institution experience.

Large cell neuroendocrine carcinoma (LCNEC) is a rare and highly invasive lung cancer subtype with an overall poor prognosis. Due to its low incidence rate and unusual pathological features, the clinical management of LCNEC remains controversial. The present study aimed to assess the effect of immune checkpoint inhibitors (ICIs) on treatment response and survival outcomes in patients with advanced LCNEC. The clinical data from 148 patients with LCNEC treated with ICIs at The First Affiliated Hospital of Zhengzhou University (Zhengzhou, China) between January 2019 and September 2021 were retrospectively analyzed. Kaplan-Meier and multivariable Cox regression analyses were used to evaluate associations between clinicopathological variables and patient outcomes. Patients treated with ICIs demonstrated extended median overall survival (mOS) times [23.5 months; 95% confidence interval (CI), 18.524-28.476] compared with patients who did not receive ICIs (11.2 months; 95% CI, 4.530-18.930) (P<0.001). Univariate analysis revealed that histological subtype (P=0.043), lymph node metastases (P=0.032) and number of metastatic organs (P=0.009) were associated with a poor prognosis. The heterogeneity of pathological components was associated with prognosis, and the mOS time was shorter for mixed LCNEC than that for pure LCNEC (P=0.043). The median progression-free survival (mPFS) (9.78 vs. 9.37 months; P=0.82) and mOS (20.70 vs. 25.79 months; P=0.181) times showed no significant association with regard to different regimens of immuno-based combination therapy (chemotherapy combined with ICIs vs. anti-angiogenic agents combined with ICIs). Poor Eastern Cooperative Oncology Group performance status score (P=0.04), multiple organ metastases (P=0.02) and high cancer antigen 125 levels (P=0.01) were independent risk factors of a poor prognosis. The present findings offer valuable insights into potential prognostic markers and highlight the favorable impact of ICIs on OS in advanced LCNEC. Prospective clinical studies are required to validate the therapeutic value of ICIs in LCNEC.

Photoelectron velocity map imaging spectroscopy of group 14 elements and iron tetracarbonyl anionic clusters MFe(CO)4- (M = Si, Ge, Sn).

The heteronuclear group 14 M-iron tetracarbonyl clusters MFe(CO)4- (M = Si, Ge, Sn) anions have been generated in the gas phase by laser ablation of M-Fe alloys and detected by mass and photoelectron spectroscopy. With the support of quantum chemical calculations, the geometric and electronic structures of MFe(CO)4- (M = Si, Ge, Sn) are elucidated, which shows that all the MFe(CO)4- clusters have the M-Fe bonded, iron-centered, and carbonyl-terminal M-Fe(CO)4 structure with the C2v symmetry and a 2B2 ground state. The M-Fe bond can be considered a double bond, which includes one σ electron sharing bond and one π dative bond. The C-O bonds in those anionic clusters are calculated to be elongated to different extents, and in particular, the C-O bonds in SiFe(CO)4- are elongated more. The Si-Fe alloy thus turns out to be a better collocation to activate the C-O bonds in the gas phase among group 14. The present findings have important implications for the rational development of high-performance catalysts with isolated metal atoms/clusters dispersed on supports.