A colloidal gold immunochromatographic method for rapid screening of imidacloprid residues in Chinese herbal medicines.

An imidacloprid colloidal gold immunochromatographic strip was developed in this work, and systematic analytical conditions were deeply investigated. The test strips were used for rapid screening of imidacloprid residues in Chinese herbal medicines. The performance of the colloidal gold test strips was investigated by using five selected Chinese herbal medicines (malt, Coix seed, lotus seed, dried ginger and honeysuckle). As a result, the developed imidacloprid colloidal gold immunochromatographic test strips could be used for rapid screening of imidacloprid residues in 60 kinds of different herbs (including 26 kinds of root/rhizome medicines, 20 kinds of seed/fruit/pericarp medicines, 11 kinds of flower/leaf/whole herb medicines, and 3 kinds of bark/aboveground issues of herb medicines), and the cut-off value was 50 µg/kg. The development of this method can achieve the goal of on-site, rapid and low-cost screening of imidacloprid residues in different herbs, which is of great significance for the quality assurance of herbs.

MAMILNet: advancing precision oncology with multi-scale attentional multi-instance learning for whole slide image analysis.

Background: Whole Slide Image (WSI) analysis, driven by deep learning algorithms, has the potential to revolutionize tumor detection, classification, and treatment response prediction. However, challenges persist, such as limited model generalizability across various cancer types, the labor-intensive nature of patch-level annotation, and the necessity of integrating multi-magnification information to attain a comprehensive understanding of pathological patterns. Methods: In response to these challenges, we introduce MAMILNet, an innovative multi-scale attentional multi-instance learning framework for WSI analysis. The incorporation of attention mechanisms into MAMILNet contributes to its exceptional generalizability across diverse cancer types and prediction tasks. This model considers whole slides as "bags" and individual patches as "instances." By adopting this approach, MAMILNet effectively eliminates the requirement for intricate patch-level labeling, significantly reducing the manual workload for pathologists. To enhance prediction accuracy, the model employs a multi-scale "consultation" strategy, facilitating the aggregation of test outcomes from various magnifications. Results: Our assessment of MAMILNet encompasses 1171 cases encompassing a wide range of cancer types, showcasing its effectiveness in predicting complex tasks. Remarkably, MAMILNet achieved impressive results in distinct domains: for breast cancer tumor detection, the Area Under the Curve (AUC) was 0.8872, with an Accuracy of 0.8760. In the realm of lung cancer typing diagnosis, it achieved an AUC of 0.9551 and an Accuracy of 0.9095. Furthermore, in predicting drug therapy responses for ovarian cancer, MAMILNet achieved an AUC of 0.7358 and an Accuracy of 0.7341. Conclusion: The outcomes of this study underscore the potential of MAMILNet in driving the advancement of precision medicine and individualized treatment planning within the field of oncology. By effectively addressing challenges related to model generalization, annotation workload, and multi-magnification integration, MAMILNet shows promise in enhancing healthcare outcomes for cancer patients. The framework's success in accurately detecting breast tumors, diagnosing lung cancer types, and predicting ovarian cancer therapy responses highlights its significant contribution to the field and paves the way for improved patient care.

Gkongensin A, an HSP90ß inhibitor, improves hyperlipidemia, hepatic steatosis, and insulin resistance.

The prevalence of obesity and its primary associated comorbidities, such as type 2 diabetes and fatty liver disease, has reached epidemic proportions, with no successful treatment available at present. Heat shock protein 90 (HSP90), a crucial chaperone, plays a key role in de novo lipogenesis (DNL) by stabilizing and maintaining sterol regulatory element binding protein (SREBP) activity. Kongensin A (KA), derived from Croton kongensis, inhibits RIP3-mediated necrosis, showing promise as an anti-necrotic and anti-inflammatory agent. It is not yet clear if KA, acting as an HSP90 inhibitor, can enhance hyperlipidemia, hepatic steatosis, and insulin resistance in obese individuals by controlling lipid metabolism. In this study, we first found that KA can potentially decrease lipid content at the cellular level. C57BL/6J mice were given a high-fat diet (HFD) and received KA and lovastatin through oral administration for 7 weeks. KA improved hyperlipidemia, fatty liver, and insulin resistance, as well as reduced body weight in diet-induced obese (DIO) mice, with no significant alteration in food intake. In vitro, KA suppressed DNL and reduced the amounts of mSREBPs. KA promoted mSREBP degradation via the FBW7-mediated ubiquitin-proteasome pathway. KA decreased the level of p-Akt Ser308, and p-GSK3ß Ser9 by inhibiting the interaction between HSP90ß and Akt. Overall, KA enhanced hyperlipidemia, hepatic steatosis, and insulin resistance by blocking SREBP activity, thereby impacting the FBW7-controlled ubiquitin-proteasome pathway.

TRIM67 interacts with ENAH to regulate the apoptosis and autophagy of lung cancer cells.

The aim of this study was to further clarify the functional mechanism of the triangular 67 (TRIM67) gene in lung cancer cells. We detected the expression of TRIM67 in lung cancer cells by RT-qPCR and Western blot, transfected si-NC, si-TRIM67, and pcDNA-ENAH into the cells. The expression of TRIM67 and ENAH was detected by Western blot and immunofluorescence localization, and CO-IP and GST pull-down experiments verified the interaction. Flow cytometry, Western blot, and transmission electron microscopy (TEM) evaluated the apoptosis and autophagy levels. TRIM67 was highly expressed in lung cancer cell lines. Knockdown of TRIM67 promoted apoptosis and autophagy of A549 and NCI-H1299 cells. TRIM67 interacted with the ENAH protein. ENAH restored the effect of knocking down TRIM67 and further inhibited apoptosis and autophagy of A549 and NCI-H1299 cells. TRIM67 inhibits apoptosis and autophagy of lung cancer cells by interacting with ENAH.

Alzheimer's therapeutic development: shifting neurodegeneration to neuroregeneration.

Alzheimer's disease (AD), similar to AD-related dementias, is characterized by impaired/lost neuronal structures and functions due to a long progression of neurodegeneration. Derailed endogenous signal pathways and disease processes have critical roles in neurodegeneration and are pharmacological targets in inducing neuroregeneration. Pharmacologically switching/shifting the brain status from neurodegeneration to neuroregeneration is emerging as a new therapeutic concept, one that is not only achievable, but also essential for effective therapy for AD. The results of the pharmacological-induced shift from neurodegeneration to neuroregeneration are twofold: arresting cognitive deterioration (and directing the brain toward cognitive recovery) in established AD, and preventing neurodegeneration through building up cognitive resilience in patients with preclinical or probable AD. In this review, we discuss these new developments in AD pharmacology and relevant clinical trials.

Habitat Radiomics Based on MRI for Predicting Platinum Resistance in Patients with High-Grade Serous Ovarian Carcinoma: A Multicenter Study.

RATIONALE AND OBJECTIVES: This study aims to explore the feasibility of MRI-based habitat radiomics for predicting response of platinum-based chemotherapy in patients with high-grade serous ovarian carcinoma (HGSOC), and compared to conventional radiomics and deep learning models. MATERIALS AND METHODS: A retrospective study was conducted on HGSOC patients from three hospitals. K-means algorithm was used to perform clustering on T2-weighted images (T2WI), contrast-enhanced T1-weighted images (CE-T1WI), and apparent diffusion coefficient (ADC) maps. After feature extraction and selection, the radiomics model, habitat model, and deep learning model were constructed respectively to identify platinum-resistant and platinum-sensitive patients. A nomogram was developed by integrating the optimal model and clinical independent predictors. The model performance and benefit was assessed using the area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI). RESULTS: A total of 394 eligible patients were incorporated. Three habitats were clustered, a significant difference in habitat 2 (weak enhancement, high ADC values, and moderate T2WI signal) was found between the platinum-resistant and platinum-sensitive groups (P < 0.05). Compared to the radiomics model (0.640) and deep learning model (0.603), the habitat model had a higher AUC (0.710). The nomogram, combining habitat signatures with a clinical independent predictor (neoadjuvant chemotherapy), yielded a highest AUC (0.721) among four models, with positive NRI and IDI. CONCLUSION: MRI-based habitat radiomics had the potential to predict response of platinum-based chemotherapy in patients with HGSOC. The nomogram combining with habitat signature had a best performance and good model gains for identifying platinum-resistant patients.

MicroRNA-221-3p promotes post-burn HUVEC proliferation, migration, and angiogenesis by regulating CDKN1B.

BACKGROUND AND OBJECTIVE: Previous studies have shown that miR-221-3p plays an important role in vascular remodeling, but it is unclear whether it contributes to angiogenesis after burn injury. The purpose of this study was to investigate the effect of miR-221-3p on angiogenesis in HUVECs after burn injury and to reveal its underlying molecular mechanism. METHODS: The burn HUVECs model was established by heat treatment. Plasmid or oligonucleotide transfection altered the expression of miR-221-3p and CDKN1B in HUVECs. MTT, colony formation, Transwell, flow cytometry, and tube formation experiments were applied to assess the proliferation, migration, apoptosis, cell cycle, and tube formation capacity of HUVECs. miR-221-3p, CDKN1B, Ki-67, and PCNA expression was assessed by RT-qPCR or Western blot. The dual-luciferase reporter assay verified the targeting relationship between miR-221-3p and CDKN1B. RESULTS: miR-221-3p was lowly expressed and CDKN1B was highly expressed in burn HUVECs. Overexpression of miR-221-3p promoted the proliferation, migration, and tube formation ability of burn HUVECs and inhibited apoptosis and the proportion of cells in the G0/G1 phase, whereas overexpression of CDKN1B had the opposite effect. Knockdown of miR-221-3p further inhibited the angiogenic capacity of burn HUVECs, but this effect was reversed by knockdown of CDKN1B. Mechanistically, miR-221-3p targeted CDKN1B. CONCLUSION: miR-221-3p improves the angiogenesis of burn HUVECs by targeting CDKN1B expression, and the miR-221-3p/CDKN1B axis may serve as a potential molecular target for future burn therapy.

Myocardial injury and related mortality in hospitalized patients with COVID-19 during the Omicron pandemic: new perspectives and insights.

Myocardial injury is one of the most common comorbidity in SARS-CoV-2 infected patients, and has poor prognosis. However, the incidence of myocardial injury in patients with SARS-CoV-2 infection has not been sufficiently investigated during the Omicron wave. We conducted a retrospective study of 2690 patients with confirmed SARS-CoV-2 Omicron infection from Tongji Hospital. The results indicated that the myocardial injury accounted for 30.8% of the total patients with SARS-CoV-2 infection and was associated with higher in-hospital mortality than those without injury before and after propensity score matching (PSM) [adjusted hazard ratio (HR), 10.61; 95% confidence interval (CI), 7.76-14.51; P â€‹< â€‹0.001; adjusted HR, 2.70; 95% CI, 1.86-3.93; P â€‹< â€‹0.001; respectively]. Further, the levels of cytokines (IL-1ß, IL-6, IL-10, and TNF-α) in patients with myocardial injury were higher than those without injury, and the higher levels of cytokines in the myocardial injury group were associated with increased mortality. Administration of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEI/ARB) could significantly reduce the mortality in patients with myocardial injury (adjusted HR, 0.52; 95% CI, 0.38-0.71; P â€‹< â€‹0.001). Additionally, the level of angiotensin II increased in patients with SARS-CoV-2 infection was even higher in myocardial injury group compared to those without injury. Collectively, the study summarized the clinical characteristic and outcome of SARS-CoV-2 infected patients with myocardial injury during the Omicron wave in China, and validated the protective role of ACEI/ARB in improving the survival of those with myocardial injury.

Advanced Alzheimer's Disease Patients Show Safe, Significant, and Persistent Benefit in 6-Month Bryostatin Trial.

BACKGROUND: In pre-clinical studies, Bryostatin, MW (molecular weight) 904, has demonstrated synaptogenic, anti-apoptotic, anti-amyloid, and anti-tau tangle efficacies. OBJECTIVE: To identify AD patients who show significant cognitive benefit versus placebo when treated in a trial with chronic Bryostatin dosing. METHODS: In this 6-month 122 AD patient Bryostatin trial, there were two cohorts: the Moderate Cohort (MMSE, Mini-Mental Status Exam: 15-18) and the Moderately Severe Cohort (MMSE 10-14) as pre-specified secondary endpoints. Patient randomization was stratified by baseline SIB to insure balance in baseline cognitive ability between treatment arms. RESULTS: With no safety events noted by the data safety and monitoring board, the Moderately Severe (MMSE 10-14) Bryostatin-treated patients were significantly improved above the placebo patients for Weeks #13 through Week #42. After two cycles of 7 x i.v. Bryostatin doses over a 26-week period, the 10-14 Cohort Severe Impairment Battery (SIB), measured every 2 weeks, showed significant benefit using a Mixed Model Repeated Measures model (MMRM, 2-tailed, p < 0.05) for Weeks #13 through #42, even 16 weeks after dosing completion by Week #26. Placebo 10-14 patients showed no benefit, declining to negative 12.8 points by Week #42. Trend analyses confirmed the MMRM data for this Cohort, with a significant downward slope (equivalent to Cognitive Decline) for the placebo group, p < 0.001, 2-tailed, but no significant decline for the Bryostatin-treated group (p = 0.409, NS), treatment versus placebo p < 0.007. The Moderate Cohort patients showed no significant benefit. CONCLUSIONS: The Bryostatin-treated MMSE 10-14 patients showed no significant cognitive decline throughout the 10-month trial, versus placebo patients' decline of -12.8 SIB points.

Insights into the intestinal toxicity of foodborne mycotoxins through gut microbiota: A comprehensive review.

Mycotoxins, which are fungal metabolites, pose a significant global food safety concern by extensively contaminating food and feed, thereby seriously threatening public health and economic development. Many foodborne mycotoxins exhibit potent intestinal toxicity. However, the mechanisms underlying mycotoxin-induced intestinal toxicity are diverse and complex, and effective prevention or treatment methods for this condition have not yet been established in clinical and animal husbandry practices. In recent years, there has been increasing attention to the role of gut microbiota in the occurrence and development of intestinal diseases. Hence, this review aims to provide a comprehensive summary of the intestinal toxicity mechanisms of six common foodborne mycotoxins. It also explores novel toxicity mechanisms through the "key gut microbiota-key metabolites-key targets" axis, utilizing multiomics and precision toxicology studies with a specific focus on gut microbiota. Additionally, we examine the potential beneficial effects of probiotic supplementation on mycotoxin-induced toxicity based on initial gut microbiota-mediated mycotoxicity. This review offers a systematic description of how mycotoxins impact gut microbiota, metabolites, and genes or proteins, providing valuable insights for subsequent toxicity studies of mycotoxins. Furthermore, it lays a theoretical foundation for preventing and treating intestinal toxicity caused by mycotoxins and advancing food safety practices.

COVID-19 infection with complicated fulminant myocarditis: a case report.

Herein, we report the case of a young female patient who suffered from myositis and heart failure due to fulminant myocarditis induced by the 2019 coronavirus disease (COVID-19). After receiving intra-aortic balloon pump (IABP) and immunomodulatory treatment, her vital signs gradually stabilized and the IABP was removed. Cardiac and muscle magnetic resonance imaging confirmed extensive myocardial and skeletal muscle edema. Though it is not uncommon for COVID-19 infection to be complicated by myocarditis and myositis, such serious muscle injury warrants clinical vigilance.

[Methodology for adaptive decision--making research on manufacturing process of traditional Chinese medicine based on deep reinforcement learning].

The manufacturing process of traditional Chinese medicine is subject to material fluctuation and other uncertain factors which usually cause non-optimal state and inconsistent product quality. Therefore, it is necessary to design and collect the quality-rela-ted physical parameters, process parameters, and equipment parameters in the whole manufacturing process of traditional Chinese medicine for digitization and modeling of the process. In this paper, a method for non-optimal state identification and self-recovering regulation was developed for active quality control in the manufacturing process of traditional Chinese medicine. Moreover, taking vacuum belt drying process as an example, a DQN algorithm-based intelligent decision model was established and verified and the implementation process was also discussed and studied. Thus, the process parameters-based self-optimization strategy discovery and path planning of optimal process control were rea-lized in this study. The results showed that the deep reinforcement learning-based artificial intelligence technology was helpful to improve the product quality consistency, reduce production cost, and increase benefit.

Small cell lung cancer transformation after EGFR-TKIs treatment in lung adenocarcinoma: A case report and literatures review.

RATIONALE: Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are commonly used in the treatment of advanced non-small cell lung cancer. However, patients will inevitably develop resistance to EGFR-TKIs in the long-term treatment process. In this paper, we report a case of small cell lung cancer transformation after EGFR-TKIs treatment in lung adenocarcinoma. We summarize the characteristics of this case and the treatment after transformation, and emphasized the repeat biopsy and dynamic monitoring its genetic mutation was necessary. PATIENT CONCERNS: A 75-years-old man with no smoking history was admitted to our hospital with repeated cough and expectoration for 1 month and chest enhancement computed tomography showed paracbronchial soft tissue mass in the lower lobe of the left lung, which was considered to be central lung cancer. DIAGNOSES: The first pathological analysis of lung biopsy confirmed left lung adenocarcinoma and clinical stage was T3N3M1 IVA. In June 2021, the second bronchoscopic biopsy was performed, and pathology showed small cell neuroendocrine carcinoma in the left lung. INTERVENTIONS: Gefitinib was given to patients when the first next generation sequence test showed EGFR L858 mutation. When the second next generation sequence test revealed EGFR T790M mutation, the patient received with osimertinib. The patient got 2 cycles chemotherapy of etoposide plus netaplatin when diagnosed with small cell lung cancer. OUTCOMES: Progression-free survival was only 8 months after gefitinib treatment. Moreover, the patient was insensitive to Oxitinib, and the disease progressed after 2 months of treatment with Oxitinib. Finally, he died of severe infection and hepatic failure after a diagnosis of small cell lung cancer. LESSONS: Our case highlights that if a patient has rapid disease progression, increase of serum neuron-specific enolase, and TP53 and Rb1 inactivation during EGFR-TKIs treatment, we should be alert to the pathological type transformation to small cell lung cancer.

Bond-selective fluorescence imaging with single-molecule sensitivity.

Bioimaging harnessing optical contrasts and chemical specificity is of vital importance in probing complex biology. Vibrational spectroscopy based on mid-infrared (mid-IR) excitation can reveal rich chemical information about molecular distributions. However, its full potential for bioimaging is hindered by the achievable sensitivity. Here, we report bond selective fluorescence-detected infrared-excited (BonFIRE) spectral microscopy. BonFIRE employs two-photon excitation in the mid-IR and near-IR to upconvert vibrational excitations to electronic states for fluorescence detection, thus encoding vibrational information into fluorescence. The system utilizes tuneable narrowband picosecond pulses to ensure high sensitivity, biocompatibility, and robustness for bond-selective biological interrogations over a wide spectrum of reporter molecules. We demonstrate BonFIRE spectral imaging in both fingerprint and cell-silent spectroscopic windows with single-molecule sensitivity for common fluorescent dyes. We then demonstrate BonFIRE imaging on various intracellular targets in fixed and live cells, neurons, and tissues, with promises for further vibrational multiplexing. For dynamic bioanalysis in living systems, we implement a high-frequency modulation scheme and demonstrate time-lapse BonFIRE microscopy of live HeLa cells. We expect BonFIRE to expand the bioimaging toolbox by providing a new level of bond-specific vibrational information and facilitate functional imaging and sensing for biological investigations.

Research progress on near-infrared long persistent phosphor materials in biomedical applications.

After excitation is stopped, long persistent phosphor materials (LPPs) can emit light for a long time. The most important feature is that it allows the separation of excitation and emission in time. Therefore, it plays a vital role in various fields such as data storage, information technology, and biomedicine. Owing to the unique mechanism of storage and luminescence, LPPs can avoid the interference of sample autofluorescence, as well as show strong tissue penetration ability, good afterglow performance, and rich spectral information in the near-infrared (NIR) region, which provides a broad prospect for the application of NIR LPPs in the field of biomedicine. In recent years, the development and applications in biomedical fields have been advanced significantly, such as biological imaging, sensing detection, and surgical guidance. In this review, we focus on the synthesis methods and luminescence mechanisms of different types of NIR LPPs, as well as their applications in bioimaging, biosensing detection, and cancer treatment in the field of biomedicine. Finally, future prospects and challenges of NIR LPPs in biomedical applications are also discussed.

The Function and Therapeutic Implications of TNF Signaling in MDSCs.

Myeloid-derived suppressor cells (MDSCs) are a group of immature and heterogeneous myeloid cells with immunosuppressive functions. MDSCs play important roles in the pathogenesis of cancer, chronic inflammatory diseases, and many autoimmune disorders. The accumulation and activation of MDSCs can be regulated by tumor necrosis factor α (TNF-α). In this review, we summarize the roles played by TNF-α in the recruitment, immunosuppressive functions, and chemotaxis of MDSCs, and discuss the potential therapeutic effects of TNF-α upon these cells in tumor growth and some inflammatory disorders.

Comprehensive analyses of genomic features and mutational signatures in adenosquamous carcinoma of the lung.

Adenosquamous carcinoma (ASC) of the lung is a relatively rare tumor with strong aggressiveness and poor prognosis. The analysis of mutational signatures is becoming routine in cancer genomics and has implications for pathogenesis, classification, and prognosis. However, the distribution of mutational signatures in ASC patients has not been evaluated. In this study, we sought to reveal the landscape of genomic mutations and mutational signatures in ASC. Next-generation sequencing (NGS) technology was used to retrieve genomic information for 124 ASC patients. TP53 and EGFR were the most prevalent somatic mutations observed, and were present in 66.9% and 54.8% of patients, respectively. CDKN2A (21%), TERT (21%), and LRP1B (18.5%) mutations were also observed. An analysis of gene fusion/rearrangement characteristics revealed a total of 64 gene fusions. The highest frequency of variants was determined for ALK fusions, with six ALK-EML4 classical and two intergenic ALK fusions, followed by three CD74-ROS1 fusions and one ROS1-SYN3 fusion. EGFR 19del (45.6%), and EGFR L858R (38.2%) and its amplification (29.4%) were the top three EGFR mutations. We extracted mutational signatures from NGS data and then performed a statistical analysis in order to search for genomic and clinical features that could be linked to mutation signatures. Amongst signatures cataloged at COSMIC, the most prevalent, high-frequency base changes were for C > T; and the five most frequent signatures, from highest to lowest, were 2, 3, 1, 30, and 13. Signatures 1 and 6 were determined to be associated with age and tumor stage, respectively, and Signatures 22 and 30 were significantly related to smoking. We additionally evaluated the correlation between tumor mutational burden (TMB) and genomic variations. We found that mutations ARID2, BRCA1, and KEAP1 were associated with high TMB. The homologous recombination repair (HRR) pathway-related gene mutation displayed a slightly higher TMB than those without mutations. Our study is the first to report comprehensive genomic features and mutational signatures in Chinese ASC patients. Results obtained from our study will help the scientific community better understand signature-related mutational processes in ASC.

Variant Angina is Associated with Myocarditis.

Background: Vasospastic angina (VSA) is caused by severe diffuse or segmental coronary artery spasms. Patients with variant angina have poor clinical outcomes, although nitrates and calcium blockers help improve patient symptoms because there is no understanding of the etiology and causal treatment. The present study investigated whether VSA is associated with inflammation of the heart. Patients and Methods: A total of 109 patients with VSA diagnosed by the presence of recurrent angina pectoris, typical electrocardiography, and coronary angiography were recruited, and 61 normal participants and 61 patients with acute myocardial infarction (AMI) and coronary artery stenosis were recruited as controls. The plasma levels of 24 cytokines were measured using a magnetic Luminex assay, and endothelin-1 and histamine levels tested using enzyme-linked immunosorbent assay and mass-spectrometry, respectively, for all participants. Furthermore, four patients with VSA underwent 18-fluorine fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT). Results: The plasma levels of interleukin (IL)-12p70, IL-13, PDL-1, IL-10, IL-6, IL-15, macrophage inflammatory protein (MIP)-1α, and MIP-1ß in patients with VSA were significantly higher than those in both normal controls and patients with AMI (p<0.001) but did not differ between normal controls and patients with AMI. 18F-FDG PET/CT showed that the left ventricle, coronary perivascular tissue volume, and coronary perivascular FDG uptake were significantly increased in all four patients. Conclusion: Our findings demonstrate that VSA patients have significantly elevated plasma cytokine levels and myocardial and pericoronary inflammation, suggesting that VSA is associated with myocarditis. This study provides novel insights into the etiology and treatment of VSA.

[Construction of knowledge base of Chinese medicine manufacturing].

Chinese medicine pharmaceutical industry is in the process of digital and intelligent transformation. Intelligent methods are required for efficient analysis and mining of the valuable information in the history data including literature data, pharmaceutical big data, and expert knowledge. Therefore, it is urgent to establish a knowledge-driven intelligent system of pharmaceutical technologies of Chinese medicine for efficient supplying of high-quality Chinese medicinal products. The present study proposed the construction method of the knowledge base of Chinese medicine manufacturing, which was preliminarily established from literature mining, case-based reasoning, and real-time prediction based on vacuum belt drying process optimization. Integrating the technologies(such as deep learning, case-based reasoning, and simulation modeling), pharmaceutical mechanisms, and big data, the knowledge base of Chinese medicine manufacturing can realize knowledge automation and scientific decision-making. It provides an example for upgrading from experience-based manufacturing to intelligent Chinese medicine manufacturing.

Label-free Super-resolution Imaging Enabled by Vibrational Imaging of Swelled Tissue and Analysis.

The universal utilization of fluorescence microscopy, especially super-resolution microscopy, has greatly advanced knowledge about modern biology. Conversely, the requirement of fluorophore labeling in fluorescent techniques poses significant challenges, such as photobleaching and non-uniform labeling of fluorescent probes and prolonged sample processing. In this protocol, the detailed working procedures of vibrational imaging of swelled tissue and analysis (VISTA) are presented. VISTA circumvents obstacles associated with fluorophores and achieves label-free super-resolution volumetric imaging in biological samples with spatial resolution down to 78 nm. The procedure is established by embedding cells and tissues in hydrogel, isotropically expanding the hydrogel sample hybrid, and visualizing endogenous protein distributions by vibrational imaging with stimulated Raman scattering microscopy. The method is demonstrated on both cells and mouse brain tissues. Highly correlative VISTA and immunofluorescence images were observed, validating the protein origin of imaging specificities. Exploiting such correlation, a machine learning-based image-segmentation algorithm was trained to achieve multi-component prediction of nuclei, blood vessels, neuronal cells, and dendrites from label-free mouse brain images. The procedure was further adapted to investigate pathological poly-glutamine (polyQ) aggregates in cells and amyloid-beta (Aß) plaques in brain tissues with high throughput, justifying its potential for large-scale clinical samples.