TomoNet: A streamlined cryogenic electron tomography software pipeline with automatic particle picking on flexible lattices.

Cryogenic electron tomography (cryoET) is capable of determining in situ biological structures of molecular complexes at near-atomic resolution by averaging half a million subtomograms. While abundant complexes/particles are often clustered in arrays, precisely locating and seamlessly averaging such particles across many tomograms present major challenges. Here, we developed TomoNet, a software package with a modern graphical user interface to carry out the entire pipeline of cryoET and subtomogram averaging to achieve high resolution. TomoNet features built-in automatic particle picking and three-dimensional (3D) classification functions and integrates commonly used packages to streamline high-resolution subtomogram averaging for structures in 1D, 2D, or 3D arrays. Automatic particle picking is accomplished in two complementary ways: one based on template matching and the other using deep learning. TomoNet's hierarchical file organization and visual display facilitate efficient data management as required for large cryoET datasets. Applications of TomoNet to three types of datasets demonstrate its capability of efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures: virus-like particles, bacterial surface layers within cellular lamellae, and membranes decorated with nuclear egress protein complexes. These results demonstrate TomoNet's potential for broad applications to various cryoET projects targeting high-resolution in situ structures.

[Treatment status of tyrosine kinase inhibitor for newly-diagnosed chronic myeloid leukemia: a domestic multi-centre retrospective real-world study].

Objective: To retrospectively analyze the treatment status of tyrosine kinase inhibitors (TKI) in newly diagnosed patients with chronic myeloid leukemia (CML) in China. Methods: Data of chronic phase (CP) and accelerated phase (AP) CML patients diagnosed from January 2006 to December 2022 from 77 centers, ≥18 years old, and receiving initial imatinib, nilotinib, dasatinib or flumatinib-therapy within 6 months after diagnosis in China with complete data were retrospectively interrogated. The choice of initial TKI, current TKI medications, treatment switch and reasons, treatment responses and outcomes as well as the variables associated with them were analyzed. Results: 6 893 patients in CP (n=6 453, 93.6%) or AP (n=440, 6.4%) receiving initial imatinib (n=4 906, 71.2%), nilotinib (n=1 157, 16.8%), dasatinib (n=298, 4.3%) or flumatinib (n=532, 7.2%) -therapy. With the median follow-up of 43 (IQR 22-75) months, 1 581 (22.9%) patients switched TKI due to resistance (n=1 055, 15.3%), intolerance (n=248, 3.6%), pursuit of better efficacy (n=168, 2.4%), economic or other reasons (n=110, 1.6%). The frequency of switching TKI in AP patients was significantly-higher than that in CP patients (44.1% vs 21.5%, P<0.001), and more AP patients switched TKI due to resistance than CP patients (75.3% vs 66.1%, P=0.011). Multi-variable analyses showed that male, lower HGB concentration and ELTS intermediate/high-risk cohort were associated with lower cytogenetic and molecular responses rate and poor outcomes in CP patients; higher WBC count and initial the second-generation TKI treatment, the higher response rates; Ph(+) ACA at diagnosis, poor PFS. However, Sokal intermediate/high-risk cohort was only significantly-associated with lower CCyR and MMR rates and the poor PFS. Lower HGB concentration and larger spleen size were significantly-associated with the lower cytogenetic and molecular response rates in AP patients; initial the second-generation TKI treatment, the higher treatment response rates; lower PLT count, higher blasts and Ph(+) ACA, poorer TFS; Ph(+) ACA, poorer OS. Conclusion: At present, the vast majority of newly-diagnosed CML-CP or AP patients could benefit from TKI treatment in the long term with the good treatment responses and survival outcomes.

Structure-guided mutagenesis targeting interactions between pp150 tegument protein and small capsid protein identify five lethal and two live-attenuated HCMV mutants.

Human cytomegalovirus (HCMV) replication relies on a nucleocapsid coat of the 150 kDa, subfamily-specific tegument phosphoprotein (pp150) to regulate cytoplasmic virion maturation. While recent structural studies revealed pp150-capsid interactions, the role of specific amino-acids involved in these interactions have not been established experimentally. In this study, pp150 and the small capsid protein (SCP), one of pp150's binding partners found atop the major capsid protein (MCP), were subjected to mutational and structural analyses. Mutations to clusters of polar or hydrophobic residues along the pp150-SCP interface abolished viral replication, with no replication detected in mutant virus-infected cells. Notably, a single amino acid mutation (pp150 K255E) at the pp150-MCP interface significantly attenuated viral replication, unlike in pp150-deletion mutants where capsids degraded outside host nuclei. These functionally significant mutations targeting pp150-capsid interactions, particularly the pp150 K255E replication-attenuated mutant, can be explored to overcome the historical challenges of developing effective antivirals and vaccines against HCMV infection.

A site-resolved two-dimensional quantum simulator with hundreds of trapped ions.

A large qubit capacity and an individual readout capability are two crucial requirements for large-scale quantum computing and simulation1. As one of the leading physical platforms for quantum information processing, the ion trap has achieved a quantum simulation of tens of ions with site-resolved readout in a one-dimensional Paul trap2-4 and of hundreds of ions with global observables in a two-dimensional (2D) Penning trap5,6. However, integrating these two features into a single system is still very challenging. Here we report the stable trapping of 512 ions in a 2D Wigner crystal and the sideband cooling of their transverse motion. We demonstrate the quantum simulation of long-range quantum Ising models with tunable coupling strengths and patterns, with or without frustration, using 300 ions. Enabled by the site resolution in the single-shot measurement, we observe rich spatial correlation patterns in the quasi-adiabatically prepared ground states, which allows us to verify quantum simulation results by comparing the measured two-spin correlations with the calculated collective phonon modes and with classical simulated annealing. We further probe the quench dynamics of the Ising model in a transverse field to demonstrate quantum sampling tasks. Our work paves the way for simulating classically intractable quantum dynamics and for running noisy intermediate-scale quantum algorithms7,8 using 2D ion trap quantum simulators.

Simplified integration of optimal self-management behaviors is associated with improved HbA1c in patients with type 1 diabetes.

PURPOSE: Living with type 1 diabetes requires burdensome and complex daily diabetes self-management behaviors. This study aimed to determine the association between integrated behavior performance and HbA1c, while identifying the behavior with the most significant impact on HbA1c. METHODS: A simple and feasible questionnaire was used to collect diabetes self-management behavior in patients with type 1 diabetes (n = 904). We assessed six dimensions of behavior performance: continuous glucose monitor (CGM) usage, frequent glucose testing, insulin pump usage, carbohydrate counting application, adjustment of insulin doses, and usage of apps for diabetes management. We evaluated the association between these behaviors and HbA1c. RESULTS: In total, 21.3% of patients performed none of the allotted behavior, while 28.5% of patients had a total behavior score of 3 or more. 63.6% of patients with a behavior score ≥ 3 achieved HbA1c goal, contrasting with only 30.4% of patients with a behavior score of 0-1. There was a mean 0.54% ± 0.05% decrease in HbA1c for each 1-unit increase in total behavior score after adjustment for age, family education and diabetes duration. Each behavior was independently correlated with a lower HbA1c level, with CGM having the most significant effect on HbA1c levels. CONCLUSIONS: Six optimal self-management behaviors, especially CGM usage, were associated with improved glycemic control, emphasizing the feasibility of implementing a simplified version of DSMES in the routine clinical care. REGISTRATION NUMBER: ClinicalTrials.gov Identifier: NCT03610984.

[Automatic classification of immune-mediated glomerular diseases based on multi-modal multi-instance learning].

OBJECTIVE: To develop a multi-modal deep learning method for automatic classification of immune-mediated glomerular diseases based on images of optical microscopy (OM), immunofluorescence microscopy (IM), and transmission electron microscopy (TEM). METHODS: We retrospectively collected the pathological images from 273 patients and constructed a multi-modal multi- instance model for classification of 3 immune-mediated glomerular diseases, namely immunoglobulin A nephropathy (IgAN), membranous nephropathy (MN), and lupus nephritis (LN). This model adopts an instance-level multi-instance learning (I-MIL) method to select the TEM images for multi-modal feature fusion with the OM images and IM images of the same patient. By comparing this model with unimodal and bimodal models, we explored different combinations of the 3 modalities and the optimal methods for modal feature fusion. RESULTS: The multi-modal multi-instance model combining OM, IM, and TEM images had a disease classification accuracy of (88.34±2.12)%, superior to that of the optimal unimodal model [(87.08±4.25)%] and that of the optimal bimodal model [(87.92±3.06)%]. CONCLUSION: This multi- modal multi- instance model based on OM, IM, and TEM images can achieve automatic classification of immune-mediated glomerular diseases with a good classification accuracy.

Overcoming the preferred orientation problem in cryoEM with self-supervised deep-learning.

While advances in single-particle cryoEM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the so-called "preferred" orientation problem) remains a complication for most specimens. Existing solutions have relied on biochemical and physical strategies applied to the specimen and are often complex and challenging. Here, we develop spIsoNet, an end-to-end self-supervised deep-learning-based software to address the preferred orientation problem. Using preferred-orientation views to recover molecular information in under-sampled views, spIsoNet improves both angular isotropy and particle alignment accuracy during 3D reconstruction. We demonstrate spIsoNet's capability of generating near-isotropic reconstructions from representative biological systems with limited views, including ribosomes, ß-galactosidases, and a previously intractable hemagglutinin trimer dataset. spIsoNet can also be generalized to improve map isotropy and particle alignment of preferentially oriented molecules in subtomogram averaging. Therefore, without additional specimen-preparation procedures, spIsoNet provides a general computational solution to the preferred orientation problem.

[Analysis of the safety, accuracy, and factors influencing bleeding complications in CT-guided puncture biopsy of brain occupying lesions].

Objective: To investigate the safety and accuracy of CT-guided intracranial puncture biopsy and the possible influencing factors of postoperative bleeding complications. Methods: A case series study. A retrospective analysis was conducted on 101 patients who underwent CT-guided intracranial puncture biopsy at the First Affiliated Hospital of Zhengzhou University from January 2017 to December 2021. The basic data of patients and the safety and accuracy of CT-guided intracranial puncture biopsy were analyzed statistically. Univariate and multivariate logistic regression analysis were used to screen the influencing factors of bleeding complications in CT-guided intracranial puncture biopsy, and the bleeding complications in glioma subgroup were analyzed. Results: Among the 101 patients, 53 were males and 48 were females, aged (53.7±17.2) years. The average diameter of intracranial lesions was (3.5±1.4) cm, while the vertical distance from the lesion to the meninges was (2.4±1.7) cm. The needle's intracranial depth reached (3.2±1.8) cm, with adjustments averaging (3±1) occurrences and an average procedural duration of (40.2±12.9) minutes. Pathological diagnoses included glioma (36 cases), gliosis (3 cases), lymphoma (32 cases), metastatic tumors (7 cases), inflammatory lesions (13 cases), and 10 indeterminate cases. The positive rate of puncture pathology was 90.1% (91/101), and the diagnostic coincidence rate was 94.0% (78/83). The incidence of bleeding complications in CT-guided intracranial puncture biopsy was 26.7% (27/101), of which 23 cases had small intratoma or needle path bleeding, 4 cases had massive bleeding, and 2 cases died. The patients were divided into bleeding group (n=27) and no bleeding group (n=74), according to the presence or absence of bleeding. The results of univariate logistic regression analysis showed that thrombin time≥15 s and the number of needle adjustment were the factors affecting the occurrence of bleeding complications (both P<0.05), and the results of multivariate logistic regression showed that thrombin time≥15 s was the related factor for bleeding. Patients with thrombin time≥15 s had a 3.045 times higher risk of bleeding than those with thrombin time<15 s (OR=3.045,95%CI:1.189-7.799,P=0.020). Among the 101 patients, 36 cases of midbrain glioma were divided into low-grade glioma group (n=11) and high-grade glioma group (n=25) according to the pathological grade. Subgroup analysis showed that the risk of bleeding for high-grade gliomas was 9.231 times higher than that for low-grade gliomas (OR=9.231,95%CI:1.023-83.331,P=0.031). Conclusions: CT-guided intracranial puncture biopsy is safe and feasible with high accuracy. Complication rates are associated with thrombin time≥15 s, especially high-grade glioma, which increases the risk of postoperative bleeding.

[Inhibition of glutamatergic neurons in the dorsomedial periaqueductal gray alleviates excessive defensive behaviors of mice with post-traumatic stress disorder].

OBJECTIVE: To investigate the role of glutamatergic neurons in the dorsomedial periaqueductal grey (dmPAG) in regulating excessive defensive behaviors in mice with post-traumatic stress disorder (PTSD). METHODS: Eight-week-old male C57BL/6 mice were subjected to stereotactic injections of different recombinant adeno- associated viral vectors (rAAV2/9-CaMKII-mCherry, rAAV2/9-CaMKII-hM3Dq-mCherry and rAAV2/9-CaMKII-hM4Di-mCherry) into the bilateral dmPAG for chemogenetic activation or inhibition of the glutamatergic neurons, followed 2 weeks later by PTSD modeling by single prolonged stress. The looming test, response to whisker stimulation test and contextual fear conditioning (CFC) test were used to observe changes in defensive behaviors of the PTSD mice. The activity of glutamatergic neurons in the dmPAG were observed using immunofluorescence staining. RESULTS: Compared with the control mice, the mouse models of PTSD showed a shortened latency of flights with increased time spent in the nest, response scores of defensive behaviors and freezing time (all P<0.01). Immunofluorescence staining revealed significantly increased c-fos-positive glutamatergic neurons in the dmPAG of PTSD mice with defensive behaviors. Activation of the glutamatergic neurons in the dmPAG (in PTSD hM3Dq group) did not cause significant changes in the latency of flights or time in nest but obviously increased response scores of defensive behaviors and freezing time of the mice, whereas inhibiting the glutamatergic neurons in the dmPAG (in PTSD hM4Di group) caused the reverse changes and obviously alleviated defensive behaviors in the PTSD mice (P<0.05 or 0.01). CONCLUSION: Inhibiting the activity of glutamatergic neurons in the dmPAG can alleviate defensive behaviors in mice with PTSD.

RNA genome packaging and capsid assembly of bluetongue virus visualized in host cells.

Unlike those of double-stranded DNA (dsDNA), single-stranded DNA (ssDNA), and ssRNA viruses, the mechanism of genome packaging of dsRNA viruses is poorly understood. Here, we combined the techniques of high-resolution cryoelectron microscopy (cryo-EM), cellular cryoelectron tomography (cryo-ET), and structure-guided mutagenesis to investigate genome packaging and capsid assembly of bluetongue virus (BTV), a member of the Reoviridae family of dsRNA viruses. A total of eleven assembly states of BTV capsid were captured, with resolutions up to 2.8 Å, with most visualized in the host cytoplasm. ATPase VP6 was found underneath the vertices of capsid shell protein VP3 as an RNA-harboring pentamer, facilitating RNA packaging. RNA packaging expands the VP3 shell, which then engages middle- and outer-layer proteins to generate infectious virions. These revealed "duality" characteristics of the BTV assembly mechanism reconcile previous contradictory co-assembly and core-filling models and provide insights into the mysterious RNA packaging and capsid assembly of Reoviridae members and beyond.

Selected humanization of yeast U1 snRNP leads to global suppression of pre-mRNA splicing and mitochondrial dysfunction in the budding yeast.

The recognition of 5' splice site (5' ss) is one of the earliest steps of pre-mRNA splicing. To better understand the mechanism and regulation of 5' ss recognition, we selectively humanized components of the yeast U1 snRNP to reveal the function of these components in 5' ss recognition and splicing. We targeted U1C and Luc7, two proteins that interact with and stabilize the yeast U1 (yU1) snRNA and the 5' ss RNA duplex. We replaced the Zinc-Finger (ZnF) domain of yU1C with its human counterpart, which resulted in a cold-sensitive growth phenotype and moderate splicing defects. We next added an auxin-inducible degron to yLuc7 protein (to mimic the lack of Luc7Ls in human U1 snRNP) and found that Luc7-depleted yU1 snRNP resulted in the concomitant loss of PRP40 and Snu71 (two other essential yeast U1 snRNP proteins), and further biochemical analyses suggest a model of how these three proteins interact with each other in the U1 snRNP. The loss of these proteins resulted in a significant growth retardation accompanied by a global suppression of pre-mRNA splicing. The splicing suppression led to mitochondrial dysfunction as revealed by a release of Fe2+ into the growth medium and an induction of mitochondrial reactive oxygen species. Together, these observations indicate that the human U1C ZnF can substitute that of yeast, Luc7 is essential for the incorporation of the Luc7-Prp40-Snu71 trimer into yeast U1 snRNP, and splicing plays a major role in the regulation of mitochondrial function in yeast.

Realizing Synthetic Dimensions and Artificial Magnetic Flux in a Trapped-Ion Quantum Simulator.

Synthetic dimension is a potent tool in quantum simulation of topological phases of matter. Here we propose and demonstrate a scheme to simulate an anisotropic Harper-Hofstadter model with controllable magnetic flux on a two-leg ladder using the spin and motional states of a single trapped ion. We verify the successful simulation of this model by comparing the measured dynamics with theoretical predictions under various coupling strength and magnetic flux, and we observe the chiral motion of wave packets on the ladder as evidence of the topological chiral edge modes. We develop a quench path to adiabatically prepare the ground states for varying magnetic flux and coupling strength, and we measure the chiral current on the ladder for the prepared ground states, which allows us to probe the quantum phase transition between the Meissner phase and the vortex phase. Our work demonstrates the trapped ion as a powerful quantum simulation platform for topological quantum matter.

Atomic structures of a bacteriocin targeting Gram-positive bacteria.

Due to envelope differences between Gram-positive and Gram-negative bacteria1, engineering precision bactericidal contractile nanomachines2 requires atomic-level understanding of their structures; however, only those killing a Gram-negative bacterium are currently known3,4. Here, we report the atomic structures of an engineered diffocin, a contractile syringe-like molecular machine that kills the Gram-positive bacterium Clostridioides difficile. Captured in one pre-contraction and two post-contraction states, each structure fashions six proteins in the bacteria-targeting baseplate, two proteins in the energy-storing trunk, and a collar protein linking the sheath with the membrane-penetrating tube. Compared to contractile machines targeting Gram-negative bacteria, major differences reside in the baseplate and contraction magnitude, consistent with differences between their targeted envelopes. The multifunctional hub-hydrolase protein connects the tube and baseplate and is positioned to degrade peptidoglycan during penetration. The full-length tape measure protein forms a coiled-coil helix bundle homotrimer spanning the entire length of the diffocin. Our study offers mechanical insights and principles for designing potent protein-based precision antibiotics.

[Progress and controversy in minimally invasive approach to radical cholecystectomy for gallbladder cancer].

Surgical treatment is one of the most important forms of treatment in patients with gallbladder cancer. With the development of minimally invasive technology, the feasibility, safety and efficacy of minimally invasive approaches such as laparoscopic or robotic-assisted radical cholecystectomy for gallbladder cancer have received continuous attention.For patients with an early T-stage (Tis or T1a), laparoscopic simple cholecystectomy is safe and economical, with a good prognosis for postoperative patients, and it has been widely accepted and performed. Radical resection of advanced gallbladder cancer requires resection of the gallbladder, its liver bed, and other neighboring invaded organs, as well as clearance of regional lymph nodes, which requires experienced gallbladder cancer treatment teams to strictly grasp the indications, select appropriate patients, and formulate a good surgical strategy to ensure the therapeutic effect. Meanwhile, robot-assisted radical resection for gallbladder cancer has been performed in a few centers and shows good clinical potential, but more high-quality studies are needed to further evaluate its value in gallbladder cancer treatment.

[Analysis of the efficacy and safety of hepatic arterial infusion chemotherapy for unresectable hepatitis B-related intrahepatic cholangiocarcinoma].

Objective: To explore the efficacy and safety of hepatic arterial infusion chemotherapy(HAIC) for unresectable hepatitis B-related intrahepatic cholangiocarcinoma(ICC). Methods: This is a retrospective controlled study. Data from 140 unresectable ICC patients who received HAIC treatment at Sun Yat-sen University Cancer Center from March 2015 to June 2023 were retrospectively collected, including 72 patients in the hepatitis B surface antigen(HBsAg)negative group (43 males and 29 females, aged (59.6±9.5)years(range: 34 to 81 years)), 68 cases in the HBsAg-positive group (48 males, 20 females, aged (53.4±11.4)years(range: 29 to 82 years)). HAIC treatment used the FOLFOX regimen combined with oxaliplatin, leucovorin,and fluorouracil. The differences in effects, prognosis,and adverse reactions between the two groups of patients after HAIC treatment were analyzed. All variables were expressed as categorical data. The χ2 test or Fisher's exact probability method was used to compare between groups. The Kaplan-Meier method was used to draw survival curves. The difference of survival curve between groups were compared through the Log-rank test. Results: According to the Response Evaluation Criteria in Solid Tumors(RECIST) version 1.1,the objective response rate(ORR) of the HBsAg-negative group was 23.2%(16/69),and the ORR of the HBsAg-positive group was 40.3%(25/62). The difference in ORR between the two groups was statistically significant(χ2=4.459,P=0.035). According to the modified RECIST(mRECIST) criteria,the ORR of the HBsAg-negative group was 27.5%(19/69), and the ORR of the HBsAg-positive group was 45.2%(28/62). The difference in ORR between the two groups was statistically significant(χ2=4.410,P=0.036). The median progression-free survival(PFS) of the HBsAg-negative group and the positive group were 7.1 months(95%CI: 5.8 to 13.2 months) and 7.3 months (95%CI: 5.7 to 10.3 months), respectively, and the median overall survival(OS) were 16.3 months (95%CI: 12.5 to 33.9 months) and 15.9 months (95%CI: 9.2 to 20.7 months) respectively. There were no statistically significant differences in PFS and OS between the two groups (both P>0.05). The main serious adverse reactions of the two groups of patients included increased AST, increased ALT, thrombocytopenia,and neutropenia. There were no statistically significant differences in various adverse reactions between the two groups after HAIC treatment (all P>0.05). Conclusion: Patients with HBsAg-positive unresectable ICC are more likely to benefit from HAIC treatment.

[A multiscale carotid plaque detection method based on two-stage analysis].

OBJECTIVE: To develop a method for accurate identification of multiscale carotid plaques in ultrasound images. METHODS: We proposed a two-stage carotid plaque detection method based on deep convolutional neural network (SM-YOLO).A series of algorithms such as median filtering, histogram equalization, and Gamma transformation were used to preprocess the dataset to improve image quality. In the first stage of the model construction, a candidate plaque set was built based on the YOLOX_l target detection network, using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes. In the second stage, the Histogram of Oriented Gradient (HOG) features and Local Binary Pattern (LBP) features were extracted and fused, and a Support Vector Machine (SVM) classifier was used to screen the candidate plaque set to obtain the final detection results. This model was compared quantitatively and visually with several target detection models (YOLOX_l, SSD, EfficientDet, YOLOV5_l, Faster R-CNN). RESULTS: SM-YOLO achieved a recall of 89.44%, an accuracy of 90.96%, a F1-Score of 90.19%, and an AP of 92.70% on the test set, outperforming other models in all performance indicators and visual effects. The constructed model had a much shorter detection time than the Faster R-CNN model (only one third of that of the latter), thus meeting the requirements of real-time detection. CONCLUSION: The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.