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Gamma/delta (γδ) T cells are unconventional lymphocytes that recognize diverse ligands via somatically recombined T cell antigen receptors (γδ TCRs). The molecular mechanism by which ligand recognition initiates γδ TCR signaling, a process known as TCR triggering, remains elusive. Unlike αß TCRs, γδ TCRs are not mechanosensitive and do not require co-receptors or typical binding-induced conformational changes for triggering. Here, we show that γδ TCR triggering by nonclassical MHC class Ib antigens, a major class of ligands recognized by γδ T cells, requires steric segregation of the large cell-surface phosphatases CD45 and CD148 from engaged TCRs at synaptic close-contact zones. Increasing access of these inhibitory phosphatases to sites of TCR engagement, by elongating MHC class Ib ligands or truncating CD45/148 ectodomains, abrogates TCR triggering and T cell activation. Our results identify a critical step in γδ TCR triggering and provide insight into the core triggering mechanism of endogenous and synthetic tyrosine-phosphorylated immunoreceptors.

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In this paper, the innovative design of a robotic hand with soft jointed structure is carried out and a tendon-driven mechanism, a master-slave motor coordinated drive mechanism, a thumb coupling transmission mechanism and a thumb steering mechanism are proposed. These innovative designs allow for more effective actuation in each finger, enhancing the load capacity of the robotic hand while maintaining key performance indicators such as dexterity and adaptability. A mechanical model of the robotic finger was made to determine the application limitations and load capacity. The robotic hand was then prototyped for a set of experiments. The experimental results showed that the proposed theoretical model were reliable. Also, the fingertip force of the robotic finger could reach up to 10.3 N, and the load force could reach up to 72.8 N. When grasping target objects of different sizes and shapes, the robotic hand was able to perform the various power grasping and precision grasping in the Cutkosky taxonomy. Moreover, the robotic hand had good flexibility and adaptability by means of adjusting the envelope state autonomously.

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BACKGROUND AND AIMS: To investigate the persistence of Lugol-unstained lesions (LULs) in the esophagus detected by chromoendoscopy and explore its association with progression to malignancy. METHODS: We enrolled 647 participants from a population-based screening trial who had biopsied LULs at the baseline chromoendoscopy and underwent a chromoendoscopy reexamination after a median of 4.39 years. Cases of persistent LUL were defined as those in whom a visible LUL was observed during reexamination at the documented location (±2cm) where a LUL was detected at baseline chromoendoscopy. Logistic regression was applied to explore risk factors for the persistence of LULs. The primary outcome was clinical-stage esophageal squamous cell carcinoma (ESCC) identified over 6.78 years of follow-up and the secondary outcome was reexamination-detected severe dysplasia and above lesions (SDA). The cumulative incidence was calculated to assess the progression risk associated with the persistence of LULs. RESULTS: The proportion of participants with persistent LULs was 81.92%. Dysplasia (adjusted OR=6.16, 95%CI: 2.70 to 17.80), large LULs (adjusted OR=1.90, 95%CI: 1.18 to 3.15), and irregularly shaped LULs (adjusted OR=1.63, 95%CI: 1.03 to 2.56) at baseline were associated with an increased risk of LUL persistence. Eleven clinical-stage ESCC cases and 31 SDAs detected during reexamination were identified, all of which originated from patients with persistent LULs (Pclinical-stageESCC =0.136, Preexamination-detected SDA =0.015). CONCLUSION: The persistence of LULs is associated with progression to malignancy in the esophagus, even in individuals without dysplastic lesions. Based on this, a more efficient post-screening surveillance strategy could be established.

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PROteolysis TArgeting Chimeras (PROTACs) has recently emerged as a promising technology. However, the design of rational PROTACs, especially the linker component, remains challenging due to the absence of structure-activity relationships and experimental data. Leveraging the structural characteristics of PROTACs, fragment-based drug design (FBDD) provides a feasible approach for PROTAC research. Concurrently, artificial intelligence-generated content has attracted considerable attention, with diffusion models and Transformers emerging as indispensable tools in this field. In response, we present a new diffusion model, DiffPROTACs, harnessing the power of Transformers to learn and generate new PROTAC linkers based on given ligands. To introduce the essential inductive biases required for molecular generation, we propose the O(3) equivariant graph Transformer module, which augments Transformers with graph neural networks (GNNs), using Transformers to update nodes and GNNs to update the coordinates of PROTAC atoms. DiffPROTACs effectively competes with existing models and achieves comparable performance on two traditional FBDD datasets, ZINC and GEOM. To differentiate the molecular characteristics between PROTACs and traditional small molecules, we fine-tuned the model on our self-built PROTACs dataset, achieving a 93.86% validity rate for generated PROTACs. Additionally, we provide a generated PROTAC database for further research, which can be accessed at https://bailab.siais.shanghaitech.edu.cn/service/DiffPROTACs-generated.tgz. The corresponding code is available at https://github.com/Fenglei104/DiffPROTACs and the server is at https://bailab.siais.shanghaitech.edu.cn/services/diffprotacs.

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The sports service supply chain faces various potential risks, such as market fluctuations, logistics issues, and partner uncertainties. To address these risks effectively, this study employs a combination of fuzzy comprehensive evaluation (FCE) methods and intelligent neural networks to create an innovative risk management framework. By considering diverse uncertainties and leveraging the analytical power of intelligent neural networks, this study aims to optimize the operation of the sports service supply chain and explore the risk factors within the public service supply chain of stadiums. This framework provides policy references to promote the healthy and sustainable development of the sports service industry. The main empirical findings, based on a representative survey of experts in China, are as follows: (1) When determining the weights of risk indicators for managing the public service supply chain of stadiums using the FCE method, the customer risk indicator is of paramount importance, with a weight of 0.286, accounting for 95.2 % of the total significance; and (2) In evaluating various risk indicators of the public service supply chain of stadiums through the neural network method, the customer risk indicator scores the highest, achieving a score of 76.02. Notably, the customer complaint risk indicator scores slightly higher at 79.33. Based on these findings, the study recommends focusing on enhancing customer experience within risk management strategies. Additionally, it suggests strengthening the supervision of platforms and third-party activities to ensure the stability and efficient operation of the stadium service supply chain. This study aims to provide theoretical support and reference indicators for evaluating the public service capabilities of stadiums.

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Using noninvasive biomarkers to identify high-risk individuals prior to endoscopic examination is crucial for optimization of screening strategies for esophageal squamous cell carcinoma (ESCC). We conducted a nested case-control study based on two community-based screening cohorts to evaluate the warning value of serum metabolites for esophageal malignancy. The serum samples were collected at enrollment when the cases had not been diagnosed. We identified 74 differential metabolites and two prominent perturbed metabolic pathways, and constructed Metabolic Risk Score (MRS) based on 22 selected metabolic predictors. The MRS generated an area under the receiver operating characteristics curve (AUC) of 0.815. The model performed well for the within-1-year interval (AUC: 0.868) and 1-to-5-year interval (AUC: 0.845) from blood draw to diagnosis, but showed limited ability in predicting long-term cases (>5 years). In summary, the MRS could serve as a potential early warning and risk stratification tool for establishing a precision strategy of ESCC screening.

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Lung cancer incidence and mortality rates are increasing worldwide, posing a significant public health challenge and an immense burden to affected families. Lung cancer encompasses distinct subtypes, namely, non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). In clinical investigations, researchers have observed that neuroendocrine tumors can be classified into four types: typical carcinoid, atypical carcinoid, small-cell carcinoma, and large-cell neuroendocrine carcinoma based on their unique features. However, there exist combined forms of neuroendocrine cancer. This study focuses specifically on combined pulmonary carcinomas with a neuroendocrine component. In this comprehensive review article, the authors provide an overview of combined lung cancers and present two pathological images to visually depict these distinctive subtypes.

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PURPOSE: To evaluate the effectiveness of endoscopic screening against incidence of and mortality from esophageal squamous cell carcinoma (ESCC). METHODS: From January 2012 to September 2016, we conducted a community-based cluster randomized controlled trial involving permanent residents age 45-69 years in a high-risk region for ESCC in northern China. A total of 668 targeted villages were randomly assigned in a 1:1 ratio to the screening group (offered Lugol's chromoendoscopy) or control group (no screening). Intention-to-treat and per-protocol analyses were performed to compare esophageal cancer (EC) incidence and mortality between the two groups. The per-protocol analysis adjusted for nonadherence to the screening procedure. RESULTS: A total of 33,847 participants were included in the analysis: 17,104 in the screening group, 15,165 (88.7%) of whom underwent screening, and 16,743 in the control group. During a maximum follow-up of 9 years, EC incidence in the screening and control groups were 60.9 and 72.5 per 100,000 person-years, respectively; mortality in the screening and control groups were 29.7 and 32.4 per 100,000 person-years, respectively. Compared with the control group, the incidence and mortality of the screening group reduced by 19% (adjusted hazard ratio [aHR], 0.81 [95% CI, 0.60 to 1.09]) and 18% (aHR, 0.82 [95% CI, 0.53 to 1.26]), respectively, in the intention-to-treat analysis; and by 22% (aHR, 0.78 [95% CI, 0.56 to 1.10]) and 21% (aHR, 0.79 [95% CI, 0.49 to 1.30]), respectively, in the per-protocol analysis. CONCLUSION: With a 9-year follow-up, our trial suggests that chromoendoscopic screening induces modest reductions in EC incidence and mortality. A more efficient strategy for EC screening and subsequent patient management should be established to guarantee the effectiveness of endoscopic screening.

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Systemic sclerosis (SSc), also known as scleroderma, is an autoimmune-related connective tissue disease with a complex and unknown pathophysiological mechanism with genes association. Several articles have reported a high prevalence of thyroid disease in SSc patients, while one study suggested a potential contribution of appendicitis to the development of SSc. To investigate this causal association, we conducted Mendelian randomization (MR) analysis using instrumental variables (IVs) to assess exposure and outcome. In the MR study involving two cohorts, all analyses were conducted using the TwoSampleMR package in R (version 4.3.0). Single nucleotide polymorphisms (SNPs) meeting a statistically significant threshold of 5E-08 were included in the analysis. Multiple complementary approaches including MR-IVW, MR-Egger, weighted median, simple mode, and weighted mode were employed to estimated the relationship between the exposure and outcome. Leave-one-out analysis and scatter plots were utilized for further investigation. Based on the locus-wide significance level, all of the MR analysis consequences manifested no causal association between the risk of appendicitis with SSc (IVW OR 0.319, 95% CI 0.063-14.055, P = 0.966). Negative causal effects of autoimmune thyroiditis (AT) on SSc (IVW OR 0.131, 95% CI 0.816-1.362, P = 0.686), Graves' disease (GD) on SSc (IVW OR 0.097, 95% CI 0.837-1.222, P = 0.908), and hypothyroidism on SSc (IVW OR 1.136, 95% CI 0.977-1.321, P = 0.096) were derived. The reverse MR revealed no significant causal effect of SSc on thyroid disease. According to the sensitivity analysis, horizontal pleiotropy was unlikely to distort the causal estimates. The consequences indicated no significant association between AT, GD, and hypothyroidism with SSc. Similarly, there was no observed relationship with appendicitis.

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BACKGROUND: Clinical opportunistic screening is a cost-effective cancer screening modality. This study aimed to establish an easy-to-use diagnostic model serving as a risk stratification tool for identification of individuals with malignant gastric lesions for opportunistic screening. METHODS: We developed a questionnaire-based diagnostic model using a joint dataset including two clinical cohorts from northern and southern China. The cohorts consisted of 17,360 outpatients who had undergone upper gastrointestinal endoscopic examination in endoscopic clinics. The final model was derived based on unconditional logistic regression, and predictors were selected according to the Akaike information criterion. External validation was carried out with 32,614 participants from a community-based randomized controlled trial. RESULTS: This questionnaire-based diagnostic model for malignant gastric lesions had eight predictors, including advanced age, male gender, family history of gastric cancer, low body mass index, unexplained weight loss, consumption of leftover food, consumption of preserved food, and epigastric pain. This model showed high discriminative power in the development set with an area under the receiver operating characteristic curve (AUC) of 0.791 (95% confidence interval [CI]: 0.750-0.831). External validation of the model in the general population generated an AUC of 0.696 (95% CI: 0.570-0.822). This model showed an ideal ability for enriching prevalent malignant gastric lesions when applied to various scenarios. CONCLUSION: This easy-to-use questionnaire-based model for diagnosis of prevalent malignant gastric lesions may serve as an effective prescreening tool in clinical opportunistic screening for gastric cancer.

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With the continuous development of artificial intelligence technology, more and more computational models for generating new molecules are being developed. However, we are often confronted with the question of whether these compounds are easy or difficult to synthesize, which refers to synthetic accessibility of compounds. In this study, a deep learning based computational model called DeepSA, was proposed to predict the synthesis accessibility of compounds, which provides a useful tool to choose molecules. DeepSA is a chemical language model that was developed by training on a dataset of 3,593,053 molecules using various natural language processing (NLP) algorithms, offering advantages over state-of-the-art methods and having a much higher area under the receiver operating characteristic curve (AUROC), i.e., 89.6%, in discriminating those molecules that are difficult to synthesize. This helps users select less expensive molecules for synthesis, reducing the time and cost required for drug discovery and development. Interestingly, a comparison of DeepSA with a Graph Attention-based method shows that using SMILES alone can also efficiently visualize and extract compound's informative features. DeepSA is available online on the below web server ( https://bailab.siais.shanghaitech.edu.cn/services/deepsa/ ) of our group, and the code is available at https://github.com/Shihang-Wang-58/DeepSA .

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Tumor antigen recognition by chimeric antigen receptors (CAR) triggers phosphorylation of their cytoplasmic portions resulting in CAR-T cell activation. We and others have shown that immunoreceptor triggering depends on the formation of close synaptic contacts, determined by the span of immunoreceptor-ligand complexes, from which large inhibitory phosphatases such as CD45 are sterically excluded. Here, we show, varying CAR-antigen complex span, that CAR-T cell activation depends on a formation of close contacts with target cells. CAR-antigen complexes with a span of 4 immunoglobulin superfamily (IgSF) domains maximize CAR-T cell activation, closely matching the span of endogenous TCR-pMHC complexes. Longer CAR-antigen complexes precipitously reduced triggering and cytokine production, but notably, anti-tumor cytotoxicity was largely preserved due to a ∼10-fold lower signaling threshold for mobilization of cytolytic effector function. Increased intermembrane spacing disrupted short-spanned PD-1-PD- L1 interactions, reducing CAR-T cell exhaustion. Together, our results show that membrane positioning across the immunological synapse can be engineered to generate CAR-T cells with clinically desirable functional profiles in vitro and in vivo .

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Gamma/delta (γδ) T cells are unconventional adaptive lymphocytes that recognize structurally diverse ligands via somatically-recombined antigen receptors (γδ TCRs). The molecular mechanism by which ligand recognition initiates γδ TCR signaling, a process known as TCR triggering, remains elusive. Unlike αß TCRs, γδ TCRs are not mechanosensitive, and do not require coreceptors or typical binding-induced conformational changes for triggering. Here, we show that γδ TCR triggering by nonclassical MHC class Ib antigens, a major class of ligands recognized by γδ T cells, requires steric segregation of the large cell-surface phosphatases CD45 and CD148 from engaged TCRs at synaptic close contact zones. Increasing access of these inhibitory phosphatases to sites of TCR engagement, by elongating MHC class Ib ligands or truncating CD45/148 ectodomains, abrogates TCR triggering and T cell activation. Our results identify a critical step in γδ TCR triggering and provide insight into the core triggering mechanism of endogenous and synthetic tyrosine-phosphorylated immunoreceptors.

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INTRODUCTION: This study aimed to evaluate the impact of Lugol-unstained lesion (LUL) location on the detection yield, which may help the endoscopist select targets for biopsy. METHODS: We enrolled 1064 subjects who had LULs at the baseline screening of a population-based randomized controlled trial. There were 1166 LULs with recorded location and pathologic diagnosis, and these were used for analysis. The detection rate of severe dysplasia and above (SDA) was calculated as the number of LULs identified as SDA divided by the number of LULs biopsied. Logistic regression with a generalized estimating equation was applied to evaluate the association between the location of a given LUL and the risk of the LUL being SDA. RESULTS: The detection rate of SDA for LULs located in the lower, middle, and upper esophagus increased from 5.9% and 10.9% to 16.7%. LUL location was significantly associated with having SDA (adjusted odds ratio (OR)upper vs. lower  = 2.88, 95% confidential interval (CI) = 1.48-5.60; adjusted ORmiddle vs. lower  = 1.63, 95% CI = 0.96-2.76), and the association was stronger in subgroups with a family history of esophageal squamous cell carcinoma (ESCC) (adjusted ORupper vs. lower  = 9.72, 95% CI = 2.57-36.69; adjusted ORmiddle vs. lower  = 3.76, 95% CI = 0.93-15.21). CONCLUSIONS: Our results suggest that more attention should be paid by endoscopists to LULs in the upper and middle esophagus, particularly for individuals with a family history of ESCC.

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BACKGROUND: Current guidelines recommend only severe dysplasia and above (SDA) lesions of the esophageal squamous epithelium for clinical intervention. However, the histopathologic diagnosis derived from tissue biopsies may be subject to underestimation of severity. METHODS: 1073 participants from whom biopsies were taken at baseline chromoendoscopic examination in a population-based screening trial were enrolled in this study. The size of the Lugol-unstained lesions (LULs) was mainly analyzed. The outcome was defined as SDA lesions either identified at baseline screening, or during follow-up, collectively referred to as the cumulative risk of SDA. Multivariable logistic regression models were used to evaluate the cumulative risk of SDA. RESULTS: One hundred and forty-six SDA cases were identified in the study period. Participants with large LULs had a high cumulative incidence of SDA (cumulative incidence16-20mm : 55.88%; cumulative incidence>20mm : 76.92%) in the median of 7-year duration. LULs of large size were significantly associated with a higher cumulative risk of SDA, regardless of the pathologic diagnosis (adjusted OR16-20mmvs.≤5mm = 21.02, 95% CI: 7.56-58.47; adjusted OR>20mmvs.≤5mm = 33.62, 95% CI: 11.79-95.87). CONCLUSIONS: Results from this study suggest physician-patient shared decision-making regarding clinical treatment or intensive surveillance should be carried out for LULs >20 mm in the esophagus, regardless of the histologic diagnosis. For those with LULs of 16-20 mm, intensive surveillance would also best be considered.

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BACKGROUND AND AIM: The impact of the presence of multiple Lugol-unstained lesions (LULs) in the esophagus on the risk of having severe dysplasia and above (SDA) lesions among asymptomatic individuals is unknown. METHODS: We collected demographic factors, behavioral variables, and features of LULs from 1073 participants who were biopsied at baseline endoscopic screening in a population-based screening trial, and these individuals were followed over a median time of 7 years. Outcome events were defined as SDA identified at screening, at reexamination, or during follow-up. "Multiple LULs" were defined as ≥ 2 LULs found in the entirety of the esophagus. Multivariable logistic regression models were fitted to assess the effect of "multiple LULs" on the cumulative risk of SDA. RESULTS: There were 147 SDA cases in the current study. After adjustment for potential risk factors and endoscopic features of LULs, the presence of "multiple LULs" slightly increased the cumulative risk of having SDA with no statistical significance (adjusted odds ratio [OR] = 1.26; 95% confidence interval [CI] [0.85, 1.88]). Further stratified analysis showed that this association was strong among subjects with small LULs (≤ 5 mm) (adjusted OR = 3.29; 95% CI [1.39, 7.79]). However, no such association was observed in subjects with larger LULs (adjusted OR = 0.99; 95% CI [0.63, 1.55], P interaction  = 0.022). CONCLUSIONS: The presence of "multiple small LULs (≤ 5 mm)" in chromoendoscopy indicates a higher cumulative risk of having SDA in the esophagus. We recommend biopsies be taken and surveillance be maintained at a more active level in individuals with relatively small but multiple LULs.

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Background: Conventional universal endoscopic screening with pathology-based endoscopic re-examination for esophageal squamous cell carcinoma is in need of reform in China. We established a "two-step" precision screening strategy using two risk prediction models and have evaluated the cost-effectiveness of this precision strategy compared with the traditional strategy based on a large population-level randomized controlled trial from a healthcare provider's perspective. Methods: Four precision screening strategies with different risk cutoffs at baseline screening and endoscopic surveillance were constructed, and then compared with traditional strategy through modeling using subjects from the screening cohort of the ESECC (Endoscopic Screening for Esophageal Cancer in China) trial. Total screening costs and the number of SDA (severe dysplasia and above in lesions of the esophagus) cases were obtained to calculate the average screening cost per SDA detected, the incremental cost-effectiveness ratio (ICER) and protection rates. Sensitivity analysis was conducted to evaluate uncertainties. Results: Compared to traditional strategy, all precision screening strategies have much lower average costs for detection of one SDA case ($7,148~$11,537 vs. $14,944). In addition, precision strategies 1&2 (strategies 1,2,3,4 described below) achieved higher effectiveness (143~150 vs. 136) and higher protection rates (87.7%~92.0% vs. 83.4%) at lower cost ($1,649,727~$1,672,221 vs. $2,032,386), generating negative ICERs (-$54,666/SDA~-$25,726/SDA) when compared to the traditional strategy. The optimal strategies within different willingness-to-pay (WTP) ranges were all precision screening strategies, and higher model sensitivities were adopted as WTP increased. Conclusions: Precision screening strategy for esophageal cancer based on risk stratification is more cost-effective than use of traditional screening strategy and has practical implications for esophageal cancer screening programs in China.

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We aimed to develop an improved version of the diagnostic model predicting the risk of malignant esophageal lesions in opportunistic screening and validate it in external populations. The development set involved 10,595 outpatients receiving endoscopy from a hospital in Hua County, a high-risk region for esophageal squamous cell carcinoma in northern China. Validation set A enrolled 9453 outpatients receiving endoscopy in a non-high-risk region in southern China. Validation set B involved 17,511 residents in Hua County. The improved diagnostic model consisted of seven predictors including age, gender, family history of esophageal squamous cell carcinoma, smoking, body mass index, dysphagia, and retrosternal pain, with an area under the receiver operating characteristic curve (AUC) of 0.860 (95% confidence interval: 0.835-0.886) in the development set. Ideal discrimination ability was achieved in external validations (AUC validation set A: 0.892, 95% confidence interval: 0.858-0.926; AUC validation set B: 0.799, 95% confidence interval: 0.705-0.894). This improved model also markedly increased the detection rate of malignant esophageal lesions compared with universal screening, demonstrating great potential for use in opportunistic screening of malignant esophageal lesions in heterogeneous populations.

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BACKGROUND: Muscle fatigue is a crucial indicator to determine whether training is in place and to protect trainers. PURPOSE: To make full use of morphological information of surface EMG and ECG signals in the time domain, a new idea and method for the fatigue assessment of exercise muscles based on data fusion is proposed in this paper. METHODS: sEMG and ECG time series with the same length were obtained by signal preprocessing and sequence normalization, feature extraction of sequence tenses was realized by a deep learning network based on sequential convolution and signal fusion model of muscle fatigue evaluation was established by D-S evidence theory. EXPERIMENT: Thirty volunteers were recruited and divided into three groups. ECG signals and sEMG signals at the biceps brachii of the right upper limb were monitored in a 20-minute exercise cycle. RESULTS: The prediction result of TCN based on time domain signal is better than the commonly used KNN and SVM recognition algorithm, and the recognition accuracy of relaxed, excessive and fatigue by D-S fusion was 89%, 86%, 88.5%. The accuracy was 0.9055, 0.9494 and 0.9269, respectively. The recall rates of the three conditions were 0.9303, 0.9570 and 0.9435. The F-score of the three conditions was 0.8911, 0.8764 and 0.8837, respectively. CONCLUSION: Based on time series and time series convolutional network, sEMG and ECG fusion of motor muscle recognition method can better distinguish different state information and has certain practical value in the fields of muscle evaluation, clinical diagnosis, wearable devices and so on.

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The rational design of PROTACs is difficult due to their obscure structure-activity relationship. This study introduces a deep neural network model - DeepPROTACs to help design potent PROTACs molecules. It can predict the degradation capacity of a proposed PROTAC molecule based on structures of given target protein and E3 ligase. The experimental dataset is mainly collected from PROTAC-DB and appropriately labeled according to the DC50 and Dmax values. In the model of DeepPROTACs, the ligands as well as the ligand binding pockets are generated and represented with graphs and fed into Graph Convolutional Networks for feature extraction. While SMILES representations of linkers are fed into a Bidirectional Long Short-Term Memory layer to generate the features. Experiments show that DeepPROTACs model achieves 77.95% average prediction accuracy and 0.8470 area under receiver operating characteristic curve on the test set. DeepPROTACs is available online at a web server ( https://bailab.siais.shanghaitech.edu.cn/services/deepprotacs/ ) and at github ( https://github.com/fenglei104/DeepPROTACs ).

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