CRISPR-repressed toxin-antitoxin provides herd immunity against anti-CRISPR elements.

Prokaryotic clustered regularly interspaced short palindromic repeat (CRISPR)-Cas systems are highly vulnerable to phage-encoded anti-CRISPR (Acr) factors. How CRISPR-Cas systems protect themselves remains unclear. Here we uncovered a broad-spectrum anti-anti-CRISPR strategy involving a phage-derived toxic protein. Transcription of this toxin is normally repressed by the CRISPR-Cas effector but is activated to halt cell division when the effector is inhibited by any anti-CRISPR proteins or RNAs. We showed that this abortive infection-like effect efficiently expels Acr elements from bacterial population. Furthermore, we exploited this anti-anti-CRISPR mechanism to develop a screening method for specific Acr candidates for a CRISPR-Cas system and successfully identified two distinct Acr proteins that enhance the binding of CRISPR effector to nontarget DNA. Our data highlight the broad-spectrum role of CRISPR-repressed toxins in counteracting various types of Acr factors. We propose that the regulatory function of CRISPR-Cas confers host cells herd immunity against Acr-encoding genetic invaders whether they are CRISPR targeted or not.

The novel HLA-C*07:1089 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-C*07:1089 differs from HLA-C*07:02:01:01 by one nucleotide in exon 3.

The new analogues of ß-trans-bergamotene from endophytic fungus Nigrospora sp. E121 with yam culture medium.

Two new bicyclic sesquiterpenes,Δ9-2, 5, 11-trihydroxyl-ß-cis-bergamotene (3) and Nigrohydroin A (4), together with ten known compounds (1, 2 and 5-12) were obtained from endophytic fungus Nigrospora sp. E121. The structures were elucidated on the basis of their 1D and 2D NMR spectra and mass spectrometric data. The possible biosynthetic pathway of compounds 1, 2, 3 and 4 in Nigrospora sp. E121were reported according to literature. The phytotoxic assay results indicated that the acetyl fragment in α-acetylorcinol may contribute to the phytotoxic activity of this compound.

A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm.

We constructed an early prediction model for postoperative pulmonary complications after thoracoscopic surgery using machine learning and deep learning algorithms. The artificial intelligence prediction models were built in Python, primarily using artificial intelligencealgorithms including both machine learning and deep learning algorithms. Correlation analysis showed that postoperative pulmonary complications were positively correlated with age and surgery duration, and negatively correlated with serum albumin. Using the light gradient boosting machine(LGBM) algorithm, weighted feature engineering revealed that single lung ventilation duration, history of smoking, surgery duration, ASA score, and blood glucose were the main factors associated with postoperative pulmonary complications. Results of artificial intelligence algorithms for predicting pulmonary complications after thoracoscopy in the test group: In terms of accuracy, the two best algorithms were Logistic Regression (0.831) and light gradient boosting machine(0.827); in terms of precision, the two best algorithms were Gradient Boosting (0.75) and light gradient boosting machine (0.742); in terms of recall, the three best algorithms were gaussian naive bayes (0.581), Logistic Regression (0.532), and pruning Bayesian neural network (0.516); in terms of F1 score, the two best algorithms were LogisticRegression (0.589) and pruning Bayesian neural network (0.566); and in terms of Area Under Curve(AUC), the two best algorithms were light gradient boosting machine(0.873) and pruning Bayesian neural network (0.869). The results of this study suggest that pruning Bayesian neural network (PBNN) can be used to assess the possibility of pulmonary complications after thoracoscopy, and to identify high-risk groups prior to surgery.

Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery.

Objective: By constructing a predictive model using machine learning and deep learning technologies, we aim to understand the risk factors for postoperative intestinal obstruction in laparoscopic colorectal cancer patients, and establish an effective artificial intelligence-based predictive model to guide individualized prevention and treatment, thus improving patient outcomes. Methods: We constructed a model of the artificial intelligence algorithm in Python. Subjects were randomly assigned to either a training set for variable identification and model construction, or a test set for testing model performance, at a ratio of 7:3. The model was trained with ten algorithms. We used the AUC values of the ROC curves, as well as accuracy, precision, recall rate and F1 scores. Results: The results of feature engineering composited with the GBDT algorithm showed that opioid use, anesthesia duration, and body weight were the top three factors in the development of POI. We used ten machine learning and deep learning algorithms to validate the model, and the results were as follows: the three algorithms with best accuracy were XGB (0.807), Decision Tree (0.807) and Neural DecisionTree (0.807); the two algorithms with best precision were XGB (0.500) and Decision Tree (0.500); the two algorithms with best recall rate were adab (0.243) and Decision Tree (0.135); the two algorithms with highest F1 score were adab (0.290) and Decision Tree (0.213); and the three algorithms with best AUC were Gradient Boosting (0.678), XGB (0.638) and LinearSVC (0.633). Conclusion: This study shows that XGB and Decision Tree are the two best algorithms for predicting the risk of developing ileus after laparoscopic colon cancer surgery. It provides new insight and approaches to the field of postoperative intestinal obstruction in colorectal cancer through the application of machine learning techniques, thereby improving our understanding of the disease and offering strong support for clinical decision-making.

The antifungal metabolites from coculture of Aspergillus fumigatus and Alternaria alternata associated with Coffea arabica.

One new cyclohexenone derivative, asperfumtone A (1) along with six known compounds were obtained from the coculture of Aspergillus fumigatus and Alternaria alternata associated with Coffea arabica. The configuration of 2 was first reported in the research. The structures were determined by extensive spectroscopic analyses, and ECD calculation. Compounds 3, 4 and 7 showed significant antifungal activities against coffee phytopathogens A. alternata and Fusarium incarnatum with MICs of 1 µg/mL. Compounds 1 and 2 showed weak antifungal activities against A. alternata and F. incarnatum with MICs of 32-64 µg/mL.

Antifeedant, Antifungal Cryptic Polyketides with Six Structural Frameworks from Tea Endophyte Daldinia eschscholtzii Propelled by the Antagonistic Coculture with Phytopathogen Colletotrichum pseudomajus and Different Culture Methods.

The antagonistic coculture with tea phytopathogen Colletotrichum pseudomajus induces antifungal cryptic metabolites from isogenesis endophyte Daldinia eschscholtzii against tea phytopathogens. Sixteen new polyketides with six structural frameworks including ten cryptic ones, named coldaldols A-C (1-3), collediol (5), and daldinrins A-L (10-20 and 23), were found from the coculture of C. pseudomajus and D. eschscholtzii by different culture methods. The unique framework of compounds 11 and 12 featured a benzopyran-C7 polyketone hybrid, and compounds 13-16 were characterized by the novel benzopyran dimer. The structures were determined mainly by spectroscopic methods, including extensive one-dimensional (1D), two-dimensional (2D) NMR, high resolution electrospray ionisation mass spectroscopy (HRESIMS), ECD calculation, and single-crystal X-ray diffraction. The configuration of acyclic compounds 5 and 18 were determined by application of the universal NMR database. Most compounds showed significant antifungal activities against the tea pathogens C. pseudomajus and Alternaria sp. with MICs of 1-8 µg/mL. Compound 12 had stronger antifungal activity than that of positive drug nystatin. The ether bond at C-4 of the benzopyran derivative increased the antifungal activity. Compounds 4-9 and 11-23 showed antifeedant activities against silkworms with feeding deterrence indices of 15-100% at the concentration of 50 µg/cm2.

Nitric oxide and ion channels mediate L-cysteine-induced inhibition of colonic smooth muscle contraction.

Previous studies have suggested that L-cysteine regulates gut motility through hydrogen sulfide. However, the mechanisms involved in the L-cysteine-induced response have not been extensively studied. This study aimed to investigate the underlying mechanisms of action of L-cysteine on spontaneous contraction of rat colon. Longitudinal and circular muscle strips from rat middle colon were prepared to measure the spontaneous contractile activities of colon in an organ bath system. Whole-cell voltage-clamp techniques were applied to record the currents of L-type voltage-dependent Ca2+ channels (VDCCs) and voltage-gated K+ channels (Kv) in isolated smooth muscle cells (SMCs) from colon. L-cysteine inhibited the spontaneous contraction of longitudinal and circular muscle strips from the rat colon in a concentration-dependent manner. The inhibition induced by L-cysteine was significantly decreased by inhibitors of H2S synthesis (p < 0.05). Furthermore, the suppression induced by L-cysteine was partially attenuated by tetrodotoxin, L-NNA and glibenclamide (p < 0.05). Whole-cell voltage-clamp recordings showed that L-cysteine caused a remarkable reduction in the peak currents of VDCCs and significantly increased the membrane currents of Kv channels in isolated SMCs (p < 0.05). We concluded that L-cysteine inhibits the contractile activities of smooth muscle strips from the rat colon. The relaxation in response to L-cysteine may be in part mediated by a nitrergic pathway and by inhibiting the VDCCs in combination with a direct activation of the KV channels and KATP channels.

The antifungal metabolites isolated from maize endophytic fungus Fusarium sp. induced by OSMAC strategy.

Six new sesquiterpenes, fusarchlamols A-F (1, 2, 4-7); one new natural product of sesquiterpenoid, methyltricinonoate (3); and ten known compounds were found from Fusarium sp. cultured in two different media by the one strain many compounds strategy. The compounds (1, 2, and 4-11) were isolated from Fusarium sp. in PDB medium, and compounds (3-5, 8, and 10-17) were discovered from Fusarium sp. in coffee medium. Additionally, the configuration of 8 was first reported in the research by Mosher's method. The structures were established by 1D, 2D NMR, mass spectrometry, calculated ECD spectra, and Mosher's method. Compounds 1, 2, 6/7, 12, and 16 indicated significant antifungal activities against the phytopathogen Alternaria alternata isolated from Coffea arabica with MICs of 1 µg/mL. The investigation on the anti-phytopathogen activity of metabolites can provide lead compounds for agrochemicals.

Preparation, Chromatic Properties Analysis and Proportioning Optimization of Co-Cr-Fe-Based Black Pigment.

The utilization of Co-Cr-Fe-based black pigments bears considerable significance within the realm of commercial ceramic pigments, owing to their distinctive spinel structure, remarkable high-temperature stability, and exceptional chromatic attributes. This study delves into the synthesis of diverse black pigment configurations by employing the co-precipitation method, leveraging the interplay of these three metallic oxides. This investigation encompasses a comprehensive scrutiny of ion valences, crystal structures and parameters, colorimetric properties, and their interrelationships. The methodology integrates the response surface methodology (RSM) framework, using theoretical formulations to navigate the material ratios and elucidating the associations between the resultant compositions and color coordinate values, aligned with the CIE-Lab* colorimetric methodology. The derived predictive models yielded an optimized black pigment composition, characterized by heightened black intensity and a refined formulation.

Widespread RNA-based cas regulation monitors crRNA abundance and anti-CRISPR proteins.

CRISPR RNAs (crRNAs) and Cas proteins work together to provide prokaryotes with adaptive immunity against genetic invaders like bacteriophages and plasmids. However, the coordination of crRNA production and cas expression remains poorly understood. Here, we demonstrate that widespread modulatory mini-CRISPRs encode cas-regulating RNAs (CreRs) that mediate autorepression of type I-B, I-E, and V-A Cas proteins, based on their limited complementarity to cas promoters. This autorepression not only reduces autoimmune risks but also responds to changes in the abundance of canonical crRNAs that compete with CreR for Cas proteins. Furthermore, the CreR-guided autorepression of Cas proteins can be alleviated or even subverted by diverse bacteriophage anti-CRISPR (Acr) proteins that inhibit Cas effectors, which, in turn, promotes the generation of new Cas proteins. Our findings reveal a general RNA-guided autorepression paradigm for diverse Cas effectors, shedding light on the intricate self-coordination of CRISPR-Cas and its transcriptional counterstrategy against Acr proteins.

Age-related impairment in fear memory extinction is restored by ketamine in middle-aged mice.

Posttraumatic stress disorder (PTSD), a disabling and chronic condition after exposure to an extreme traumatic event, affects approximately 8% of the population worldwide. However, the underlying mechanisms of PTSD are not clear. The ability to manage fear memories is critical for PTSD. Differences in stress responsiveness and coping strategies by age represent an important starting point for the understanding and prevention of PTSD. However, we do not know whether the ability to cope with fear memories is decreased in middle-aged mice. To investigate this, we compared fear memory extinction among different age groups of mice. We found that middle-aged mice exhibited impaired fear memory extinction, which was accompanied by sustained enhanced long-term potentiation (LTP) induction in the extinction process. Most interestingly, ketamine treatment restored the impaired fear memory extinction in middle-aged mice. Moreover, ketamine could ameliorate the increased LTP during the extinction process through a presynaptic mechanism. Altogether, our results indicated that middle-aged mice were unable to extinguish fear memories, which could be treated with ketamine via presynaptic-mediated synaptic plasticity in middle-aged mice, suggesting that ketamine administration may be a new strategy for the treatment of PTSD.

Predicting early postoperative PONV using multiple machine-learning- and deep-learning-algorithms.

OBJECTIVE: PONV reduces patient satisfaction and increases hospital costs as patients remain in the hospital for longer durations. In this study, we build a preliminary artificial intelligence algorithm model to predict early PONV in patients. METHODS: We use R for statistical analysis and Python for the machine learning prediction model. RESULTS: Average characteristic engineering results showed that haloperidol, sex, age, history of smoking, and history of PONV were the first 5 contributing factors in the occurrence of early PONV. Test group results for artificial intelligence prediction of early PONV: in terms of accuracy, the four best algorithms were CNNRNN (0.872), Decision Tree (0.868), SVC (0.866) and adab (0.865); in terms of precision, the three best algorithms were CNNRNN (1.000), adab (0.400) and adab (0.868); in terms of AUC, the top three algorithms were Logistic Regression (0.732), SVC (0.731) and adab (0.722). Finally, we built a website to predict early PONV online using the Streamlit app on the following website: ( https://zhouchengmao-streamlit-app-lsvc-ad-st-app-lsvc-adab-ponv-m9ynsb.streamlit.app/ ). CONCLUSION: Artificial intelligence algorithms can predict early PONV, whereas logistic regression, SVC and adab were the top three artificial intelligence algorithms in overall performance. Haloperidol, sex, age, smoking history, and PONV history were the first 5 contributing factors associated with early PONV.

Associate toxin-antitoxin with CRISPR-Cas to kill multidrug-resistant pathogens.

CreTA, CRISPR-regulated toxin-antitoxin (TA), safeguards CRISPR-Cas immune systems by inducing cell dormancy/death upon their inactivation. Here, we characterize a bacterial CreTA associating with the I-F CRISPR-Cas in Acinetobacter. CreT is a distinct bactericidal small RNA likely targeting several essential RNA molecules that are required to initiate protein synthesis. CreA guides the CRISPR effector to transcriptionally repress CreT. We further demonstrate a proof-of-concept antimicrobial strategy named ATTACK, which AssociaTes TA and CRISPR-Cas to Kill multidrug resistant (MDR) pathogens. In this design, CRISPR-Cas is programed to target antibiotic resistance gene(s) to selectively kill MDR pathogens or cure their resistance, and when CRISPR-Cas is inactivated or suppressed by unwanted genetic or non-genetic events/factors, CreTA triggers cell death as the last resort. Our data highlight the diversity of RNA toxins coevolving with CRISPR-Cas, and illuminate a combined strategy of CRISPR and TA antimicrobials to 'ATTACK' MDR pathogens.

Differentiation of Bone Metastasis in Elderly Patients With Lung Adenocarcinoma Using Multiple Machine Learning Algorithms.

OBJECTIVE: We tested the performance of general machine learning and joint machine learning algorithms in the classification of bone metastasis, in patients with lung adenocarcinoma. METHODS: We used R version 3.5.3 for statistical analysis of the general information, and Python to construct machine learning models. RESULTS: We first used the average classifiers of the 4 machine learning algorithms to rank the features and the results showed that race, sex, whether they had surgery and marriage were the first 4 factors affecting bone metastasis. Machine learning results in the training group: for area under the curve (AUC), except for RF and LR, the AUC values of all machine learning classifiers were greater than .8, but the joint algorithm did not improve the AUC for any single machine learning algorithm. Among the results related to accuracy and precision, the accuracy of other machine learning classifiers except the RF algorithm was higher than 70%, and only the precision of the LGBM algorithm was higher than 70%. Machine learning results in the test group: Similarly, for areas under the curve (AUC), except RF and LR, the AUC values for all machine learning classifiers were greater than .8, but the joint algorithm did not improve the AUC value for any single machine learning algorithm. For accuracy, except for the RF algorithm, the accuracy of other machine learning classifiers was higher than 70%. The highest precision for the LGBM algorithm was .675. CONCLUSION: The results of this concept verification study show that machine learning algorithm classifiers can distinguish the bone metastasis of patients with lung cancer. This will provide a new research idea for the future use of non-invasive technology to identify bone metastasis in lungcancer. However, more prospective multicenter cohort studies are needed.

Novel Antifungal and Antifeedant Metabolites from Penicillium chrysogenum Co-Cultured with Nemania primolutea and Aspergillus fumigatus.

The endophyte Nemania primolutea, inhibited the growth of Penicillium chrysogenum in the coculture system. Four new compounds, nemmolutines A-B (1-2), and penigenumin (3) from N. primolutea, penemin (4) from P. chrysogenum were isolated from the coculture. On the other hand, P. chrysogenum inhibited the Aspergillus fumigatus in the coculture. Induced metabolites (13-16) with monasone naphthoquinone scaffolds including a new one from P. chrysogenum were produced by the coculture of P. chrysogenum, and A. fumigatus. Interesting, cryptic metabolites penicichrins A-B isolated from wild P. chrysogenum induced by host Ziziphus jujuba medium were also found in induced P. chrysogenum cultured in PDB ordinary medium. So the induction of penicichrin production by supplementing with host extract occurred in the fungus P. chrysogenum not the host medium. The productions of penicichrins were the spontaneous metabolism, and the metabolites (13-16) were the culture driven. Compounds 4, 6, 8, 10, 11, 14, and 15 showed significant antifungal activities against the phytopathogen Alternaria alternata with MICS of 1-8 µg/mL, and compounds 7, 9, and 12 indicated significant antifeedant activities against silkworms with feeding deterrence indexes (FDIs) of 92 %, 66 %, and 64 %. The carboxy group in 4-(2-hydroxybutynoxy)benzoic acid derivatives, and xylabisboeins; the hydroxy group in mellein derivatives; and the quinoid in monasone naphthoquinone increased the antifungal activities.

Antifungal and antifeedant terpenoids from Paraphaeosphaeria sp. cultured by extract of host Ginkgo biloba.

Five undescribed terpenoids including a polyketide-terpenoid hybrid paraphaone, and four eremophilane sesquiterpenoids, paraphaterpenes A-D, as well as two known compounds were isolated from the endophytic fungus Paraphaeosphaeria sp. cultured by extract of host Ginkgo biloba L. The structures were established by spectroscopic analyses, and the single-crystal X-ray diffraction. The antifungal activity of Paraphaeosphaeria sp. cultured by extract of G. biloba against the plant pathogen Alternaria alternata was significant and higher than that of PDB medium. Tested compounds indicated antifeedant activities against silkworms with feeding deterrence index at 10-70%. Paraphaone, paraphaterpenes A, C, D and alternariol methyl ether showed significant antifungal activities against the phytopathogens A. alternata, Aspergillus fumigatus, and entomopathogen Beauveria bassiana with MICs ≤4 µg/mL. And the preliminary structure-activity relationship of eremophilane sesquiterpenoids was exhibited. The culture of Paraphaeosphaeria sp. by host G. biloba medium afforded agricultural antibiotics.

Laryngeal contact granuloma after radiotherapy in patients with nasopharyngeal carcinoma: a case series.

Background: Laryngeal contact granuloma (LCG) is a benign hypertrophic lesion and phonatory injury after abnormal vocal behavior is regarded as its major etiology. Patients receiving radiation for non-laryngeal head and neck tumors are troubled by persistent voice impairment. The occurrence of LCG after radiotherapy for nasopharyngeal carcinoma (NPC) in our practice has implored us to re-exam their underlying etiology. We hypothesize that a proportion of LCG results from voice change caused by non-laryngeal head and neck cancer radiotherapy and firstly describe a distinct LCG population originated after radiotherapy for NPC with respect to the clinical profile, presentation, prognosis and response to treatment of patients. Methods: We retrospectively reviewed the laryngoscopic examination and tumor study findings to elucidate the common clinical features of patients who presented with LCG after radiotherapy for NPC. All patients were regularly monitored with telescopic examination until lesions disappeared. Data on age, sex, clinical presentation, telescopic findings, management, latency time of lesion formation, remission time and clinical outcome were reviewed. Results: The medical review identified 27 cases of LCG secondary to radiotherapy for NPC. All lesions had been diagnosed during routine endoscopy following radiation. The interval between radiation onset and endoscopic diagnosis was 3.77 months (range, 0.67-11 months). 20 cases were resolved through simple observation, 4 cases were resolved with the administration of proton pump inhibitors (PPIs), and 3 cases with a poor response to PPI therapy required subsequent surgical resection. The mean remission time in the observation and PPI groups was 4.42 months (range, 0.73-18.9 months) and 5.78 months (range, 2.17-14.63 months), respectively. All patients recovered completely and none experienced recurrence during a mean follow-up of 32.44 months (range, 5.6-71.67 months). Conclusions: Iatrogenic granulomas of vocal process are presenting after radiation for non-laryngeal head and neck cancers. In contrast with spontaneous granulomas, these granulomas can be cured at high remission rates and low recurrence trend without specific intervention. Thus, simple observation may be sufficient for radiation-induced LCG.

Antibiotic Guanacastane Diterpenoids with Two New Skeletons from Psathyrella candolleana Uncovered by Semisolid and Liquid Media.

The culture of Psathyrella candolleana in host Dioscorea opposite medium produced seven new guanacastane diterpenoids, psayamin (1) as an unprecedented 5/7/6/6/6/6/7/5-fused octacyclic spiro scaffold both under liquid and semisolid conditions, psathins A-C (4-6) with a 5/7/6 tricyclic backbone by liquid medium, psathins D-E (7-8) as the same unprecedented skeletons of 5/6/7/6-fused tetracyclic or 6/7/6 tricyclic structures, and psathin F (9) with a 5/7/5/6 tetracyclic backbone by semisolid medium. The structures were elucidated by detailed spectroscopic analyses and those of 1 and 7 were determined by single-crystal X-ray crystallography. The semisolid culture led to four structure types of the guanacastane diterpenoid. Compound 5 showed antifungal activity against phytopathogen Fusarium incarnatum with a minimum inhibitory concentration (MIC) of 8 µg/mL, while compound 4 showed significant antifungal activity against Alternaria sp. with an MIC of 2 µg/mL. Compounds 1 and 8 also showed antifeedant activities against the silkworms with the feeding deterrence indices of 50%, at the concentrations of 50 µg/cm2. Compound 1 showed significant cytotoxicity with IC50 at 10.87 ± 0.24-15.96 ± 0.30 µM and anti-acetylcholinesterase activity with IC50 at 37.3 µM. Also, compound 1 remarkably induced apoptosis of HL-60 at 10, 20 µM in a concentration-dependent manner. The spiral ring of 1 was vital in cytotoxicity and anti-acetylcholinesterase activity. The different media fermented by P. candolleana resulted in the chemical diversity of bioactive guanacastane diterpenoids and potential applications in the agricultural and food functions.

Three new fumagillol analogues and antifungal activity from Aspergillus fumigatus cocultured with Paraphaeosphaeria sp.

Two fungi Aspergillus fumigatus YXG-12-2, and Paraphaeosphaeria sp. YXG-18 were isolated from medicinal plant Ginkgo biloba. The interaction of endophytes and host could induce the productions of antifungal metabolites against pathogens for the plant resistance. Three new fumagillol analogues, fumiparaphines A-C were isolated from A. fumigatus cocultured with Paraphaeosphaeria sp. in host medium. New compounds 2, and 3 had the similar fumagillol structures with tetrahydrofuran or tetrahydropyrane residue. The structures were established by 1D, 2D NMR, mass spectrometry, and calculated ECD spectra. Fumiparaphine A (1) indicated significant antifungal activity against the phytopathogen Alternaria alternata with MIC of 2 µg/mL.