Microbes in porous environments: from active interactions to emergent feedback.

Microbes thrive in diverse porous environments-from soil and riverbeds to human lungs and cancer tissues-spanning multiple scales and conditions. Short- to long-term fluctuations in local factors induce spatio-temporal heterogeneities, often leading to physiologically stressful settings. How microbes respond and adapt to such biophysical constraints is an active field of research where considerable insight has been gained over the last decades. With a focus on bacteria, here we review recent advances in self-organization and dispersal in inorganic and organic porous settings, highlighting the role of active interactions and feedback that mediates microbial survival and fitness. We discuss open questions and opportunities for using integrative approaches to advance our understanding of the biophysical strategies which microbes employ at various scales to make porous settings habitable.

Glutamatergic neurons in the paraventricular nucleus of the hypothalamus participate in the regulation of visceral pain induced by pancreatic cancer in mice.

Background: Visceral pain induced by pancreatic cancer seriously affects patients' quality of life, and there is no effective treatment, because the mechanism of its neural circuit is unknown. Therefore, the aim of this study is to explore the main neural circuit mechanism regulating visceral pain induced by pancreatic cancer in mice. Methods: The mouse model of pancreatic cancer visceral pain was established on C57BL/6N mice by pancreatic injection of mPAKPC-luc cells. Abdominal mechanical hyperalgesia and hunch score were performed to assess visceral pain; the pseudorabies virus (PRV) was used to identify the brain regions innervating the pancreas; the c-fos co-labeling method was used to ascertain the types of activated neurons; in vitro electrophysiological patch-clamp technique was used to record the electrophysiological activity of specific neurons; the calcium imaging technique was used to determine the calcium activity of specific neurons; specific neuron destruction and chemogenetics methods were used to explore whether specific neurons were involved in visceral pain induced by pancreatic cancer. Results: The PRV injected into the pancreas was detected in the paraventricular nucleus of the hypothalamus (PVN). Immunofluorescence staining showed that the majority of c-fos were co-labeled with glutamatergic neurons in the PVN. In vitro electrophysiological results showed that the firing frequency of glutamatergic neurons in the PVN was increased. The calcium imaging results showed that the calcium activity of glutamatergic neurons in the PVN was enhanced. Both specific destruction of glutamatergic neurons and chemogenetics inhibition of glutamatergic neurons in the PVN alleviated visceral pain induced by pancreatic cancer. Conclusions: Glutamatergic neurons in the PVN participate in the regulation of visceral pain induced by pancreatic cancer in mice, providing new insights for the discovery of effective targets for the treatment of pancreatic cancer visceral pain.

Neuroinflammation in the paraventricular nucleus of the hypothalamus precipitates visceral pain induced by pancreatic cancer in mice.

Background: Given the pivotal role of neuroinflammation in chronic pain and that the paraventricular nucleus of the hypothalamus (PVN) is a crucial brain region involved in visceral pain regulation, we sought to investigate whether the targeted modulation of microglia and astrocytes in the PVN could ameliorate pancreatic cancer-induced visceral pain (PCVP) in mice. Methods: Using a mouse model of PCVP, achieved by tumor cell injection at the head of the pancreas, we measure the number of glial cells, and at the same time we employed minocycline to inhibit microglia and chemogenetic methods to suppress astrocytes in order to investigate the respective roles of microglia and astrocytes within the PVN in PCVP. Results: Mice exhibited visceral pain at 12, 15 and 18 days post-tumor cell injection. We observed a significant increase in the population of both microglia and astrocytes. Inhibition of microglial activity through minocycline microinjection into the PVN resulted in alleviation of visceral pain within 30 and 60 min. Similarly, chemogenetic inhibition of astrocyte function at 14 and 21 days post-injection also led to relief from visceral pain. Conclusions: This study found that PVN microglia and astrocytes were involved in regulating PCVP. Our results suggest that targeting glia may be a potential approach for alleviating visceral pain in patients with pancreatic cancer.

Inhibition of GABAergic neurons in the paraventricular nucleus of the hypothalamus precipitates visceral pain induced by pancreatic cancer in mice.

Background: For patients with pancreatic cancer, visceral pain is a debilitating symptom that significantly compromises their quality of life. Unfortunately, the lack of effective treatment options can be attributed to our limited understanding of the neural circuitry underlying this phenomenon. The primary objective of this study is to elucidate the fundamental mechanisms governing visceral pain induced by pancreatic cancer in murine models. Methods: A mouse model of pancreatic cancer visceral pain was established in C57BL/6N mice through the intrapancreatic injection of mPAKPC-luc cells. Abdominal mechanical hyperalgesia and hunch score were employed to evaluate visceral pain, whereas the in vitro electrophysiological patch-clamp technique was utilized to record the electrophysiological activity of GABAergic neurons. Specific neuron ablation and chemogenetics methods were employed to investigate the involvement of GABAergic neurons in pancreatic cancer-induced visceral pain. Results: In vitro electrophysiological results showed that the firing frequency of GABAergic neurons in the paraventricular nucleus of the hypothalamus (PVN) was decreased. Specific destruction of GABAergic neurons in the PVN exacerbated visceral pain induced by pancreatic cancer. Chemogenetics activation of GABAergic neurons in the PVN alleviated visceral pain induced by pancreatic cancer. Conclusions: GABAergic neurons located in PVN play a crucial role in precipitating visceral pain induced by pancreatic cancer in mice, thereby offering novel insights for identifying effective targets to treat pancreatic cancer-related visceral pain.

Development and validation of a regression model with nomogram for difficult video laryngoscopy in Chinese population: a prospective, single-center, and nested case-control study.

Background: Airway management failure is associated with increased perioperative morbidity and mortality. Airway-related complications can be significantly reduced if difficult laryngoscopy is predicted with high accuracy. Currently, there are no large-sample studies on difficult airway assessments in Chinese populations. An airway assessment model based on the Chinese population is urgently needed to guide airway rescue strategy. Methods: This prospective nested case-control study took place in a tertiary hospital in Shanghai, China. Information on 10,549 patients was collected, and 8,375 patients were enrolled, including 7,676 patients who underwent successful laryngoscopy and 699 patients who underwent difficult laryngoscopy. The baseline characteristics, medical history, and bedside examinations were included as predictor variables. Laryngoscopy was defined as 'successful laryngoscopy' based on a Cormack-Lehane Grades of 1-2 and as 'difficult laryngoscopy' based on a Cormack-Lehane Grades of 3-4. A model was developed by incorporating risk factors and was presented in the form of a nomogram by univariate logistic regression, least absolute shrinkage and selection operator, and stepwise logistic regression. The main outcome measures were area under the curve (AUC), sensitivity, and specificity of the predictive model. Result: The AUC value of the prediction model was 0.807 (95% confidence interval [CI]: 0.787-0.828), with a sensitivity of 0.730 (95% CI, 0.690-0.769) and a specificity of 0.730 (95% CI, 0.718-0.742) in the training set. The AUC value of the prediction model was 0.829 (95% CI, 0.800-0.857), with a sensitivity of 0.784 (95% CI, 0.73-0.838) and a specificity of 0.722 (95% CI, 0.704-0.740) in the validation set. Conclusion: Our model had accurate predictive performance, good clinical utility, and good robustness for difficult laryngoscopy in the Chinese population.

Geometric morphometrics and machine learning from three-dimensional facial scans for difficult mask ventilation prediction.

Background: Unanticipated difficult mask ventilation (DMV) is a potentially life-threatening event in anesthesia. Nevertheless, predicting DMV currently remains a challenge. This study aimed to verify whether three dimensional (3D) facial scans could predict DMV in patients scheduled for general anesthesia. Methods: The 3D facial scans were taken on 669 adult patients scheduled for elective surgery under general anesthesia. Clinical variables currently used as predictors of DMV were also collected. The DMV was defined as the inability to provide adequate and stable ventilation. Spatially dense landmarks were digitized on 3D scans to describe sufficient details for facial features and then processed by 3D geometric morphometrics. Ten different machine learning (ML) algorithms, varying from simple to more advanced, were introduced. The performance of ML models for DMV prediction was compared with that of the DIFFMASK score. The area under the receiver operating characteristic curves (AUC) with its 95% confidence interval (95% CI) as well as the specificity and sensitivity were used to evaluate the predictive value of the model. Results: The incidence of DMV was 35/669 (5.23%). The logistic regression (LR) model performed best among the 10 ML models. The AUC of the LR model was 0.825 (95% CI, 0.765-0.885). The sensitivity and specificity of the model were 0.829 (95% CI, 0.629-0.914) and 0.733 (95% CI, 0.532-0.819), respectively. The LR model demonstrated better predictive performance than the DIFFMASK score, which obtained an AUC of 0.785 (95% CI, 0.710-0.860) and a sensitivity of 0.686 (95% CI, 0.578-0.847). Notably, we identified a significant morphological difference in the mandibular region between the DMV group and the easy mask ventilation group. Conclusion: Our study indicated a distinct morphological difference in the mandibular region between the DMV group and the easy mask ventilation group. 3D geometric morphometrics with ML could be a rapid, efficient, and non-invasive tool for DMV prediction to improve anesthesia safety.

Smartphone-Enabled Fluorescence and Colorimetric Platform for the On-Site Detection of Hg2+ and Cl- Based on the Au/Cu/Ti3C2 Nanosheets.

Smartphone-assisted fluorescence and colorimetric methods for the on-site detection of Hg2+ and Cl- were established based on the oxidase-like activity of the Au-Hg alloy on the surface of Au/Cu/Ti3C2 NSs. The Au nanoparticles (NPs) were constructed via in-situ growth on the surface of Cu/Ti3C2 NSs and characterized by different characterization techniques. After the addition of Hg2+, the formation of Hg-Au alloys could promote the oxidization of o-phenylenediamine (OPD) to generate a new fluorescence emission peak of 2,3-diaminopenazine (ADP) at 570 nm. Therefore, a turn-on fluorescence method for the detection of Hg2+ was established. As the addition of Cl- can influence the fluorescence of ADP, the fluorescence intensity was constantly quenched to achieve the continuous quantitative detection of Cl-. Therefore, a turn-off fluorescence method for the detection of Cl- was established. This method had good linear ranges for the detection of Hg2+ and Cl- in 8.0-200.0 nM and 5.0-350.0 µM, with a detection limit of 0.8 nM and 27 nM, respectively. Depending on the color change with the detection of Hg2+ and Cl-, a convenient on-site colorimetric method for an analysis of Hg2+ and Cl- was achieved by using digital images combined with smartphones (color recognizers). The digital picture sensor could analyze RGB values in concentrations of Hg2+ or Cl- via a smartphone app. In summary, the proposed Au/Cu/Ti3C2 NSs-based method provided a novel and more comprehensive application for environmental monitoring.

Development and validation of a nomogram for difficult laryngoscopy at visual laryngoscopy: a prospective nested case-control study.

Background: Unsuccessful airway management is associated with increased perioperative morbidity and mortality. Difficult laryngoscopy is a leading cause of unanticipated difficult airways and presents a challenge for anesthesiologists. Airway ultrasound assessment can be used as a priority diagnostic strategy for difficult laryngoscopy because of its diagnostic performance in difficult airways. This study was designed to develop a comprehensive model based on multivariate statistical analysis (including bedside examination tests and ultrasonography) for difficult laryngoscopy. Methods: This study was conducted from December 27, 2021, to September 16, 2022. All patients underwent an airway ultrasonographic measurement with a standard operating procedure. The baseline characteristics and bedside examination tests were also recorded. Laryngoscopy with a Cormack-Lehane (CL) grade of 1-2 was defined as "easy laryngoscopy", whereas "difficult laryngoscopy" was based on a CL grade of 3-4. The prediction model was built by using baseline characteristics, bedside examination tests, and ultrasonographic measurements as independent variables and easy/difficult laryngoscopy as the dependent variable. Results: A total of 516 patients were eligible, and 456 patients were finally enrolled in the study. A 4-variable analysis, including inter-incisor gap (IIG), thyromental distance (TMD), the distance from the skin to the tongue root, and airway-related diseases, was performed to construct the optimum prediction model. The area under curve (AUC) value of the prediction model was 0.933 [95% confidence interval (CI): 0.770 to 0.935] in the training set and 0.956 (95% CI: 0.915 to 0.997) in the validation set. Conclusions: The comprehensive model and nomogram, especially the integration of tongue root thickness, can predict the risk of difficult laryngoscopy more accurately and reliably than any other screening method alone, allowing for reasonable individualized regimen decision-making.

Hole-initiated melting process of thin films.

We perform numerical and experimental studies on the melting process of thin films initiated by a small hole in the continuum regime. The presence of a nontrivial capillary surface, namely the liquid/air interface, leads to a few counterintuitive results: (1) The melting point is elevated if the film surface is partially wettable, even with a small contact angle. (2) For a film that is finite in size, melting may prefer to start from the outer boundary rather than a hole inside. (3) More complex melting scenarios may arise, including morphology transitions and the "de facto" melting point being a range instead of a single value. These are verified by experiments on melting alkane films between silica and air. This work continues a series of investigations on the capillary aspects of melting. Both our model and analysis approach can be easily generalized to other systems.

Flaw-insensitive fatigue resistance of chemically fixed collagenous soft tissues.

Bovine pericardium (BP) has been used as leaflets of prosthetic heart valves. The leaflets are sutured on metallic stents and can survive 400 million flaps (~10-year life span), unaffected by the suture holes. This flaw-insensitive fatigue resistance is unmatched by synthetic leaflets. We show that the endurance strength of BP under cyclic stretch is insensitive to cuts as long as 1 centimeter, about two orders of magnitude longer than that of a thermoplastic polyurethane (TPU). The flaw-insensitive fatigue resistance of BP results from the high strength of collagen fibers and soft matrix between them. When BP is stretched, the soft matrix enables a collagen fiber to transmit tension over a long length. The energy in the long length dissipates when the fiber breaks. We demonstrate that a BP leaflet greatly outperforms a TPU leaflet. It is hoped that these findings will aid the development of soft materials for flaw-insensitive fatigue resistance.

Tough and Thermostable Polybutylene Terephthalate (PBT)/Vitrimer Blend with Enhanced Interfacial Compatibility.

Polymer blending is an efficient way to obtain extraordinary polymeric materials. However, once permanently cross-linked thermosets are involved in blending, there are challenges in designing and optimizing the structures and interfacial compatibility of blends. Vitrimer with dynamic covalent polymer networks provides an innovative opportunity for blending thermoplastics and thermosets. Herein, a reactive blending strategy is proposed to develop thermoplastic-thermoset blend with enhanced compatibility on the basis of dynamic covalent chemistry. Specifically, polybutylene terephthalate (PBT) and polymerized epoxy vitrimer can be directly melt blended to obtain tough and thermostable blends with desirable microstructures and interfacial interaction. Bond exchange facilitates the grafting of PBT and epoxy vitrimer chains, thus enhancing the interfacial compatibility and thermal stability of blends. The obtained blend balances the strength and stretchability of PBT and epoxy vitrimer, resulting in enhanced toughness. This work offers a new way of designing and fabricating new polymeric materials by blending thermoplastics and thermosets. It also suggests a facile direction towards upcycling thermoplastics and thermosets.

Association of urinary bisphenol A with chronic obstructive pulmonary disease-related diseases: evidence from the National Health and Nutrition Examination Survey database (2005-2016).

In vivo and in vitro studies have found that exposure to bisphenol A (BPA) can lead to pulmonary diseases, but there exists little evidence regarding the association between urinary BPA level and chronic obstructive pulmonary disease (COPD)-related diseases in the population. National Health and Nutrition Examination Survey data, from 2005 to 2016, were utilized in this study. Participants who self-reported having emphysema, chronic bronchitis, or COPD were defined as having COPD-related diseases. A multivariate logistic regression analysis was used to analyze the association of urinary BPA with COPD-related diseases in the overall population and according to sex. Three separate models including different covariates were used in our analyses. The association of urinary BPA with COPD-related diseases in different subgroups (age, smoking status, participants belonging to "ever had asthma" and "ever had cardiovascular disease") other than sex was also analyzed. Based on the different models, 9189, 7006, and 6946 participants were used in our study. BPA was found to be significantly associated with COPD-related diseases in all models. The concentration of BPA in urine was significantly associated with COPD-related diseases regardless of whether BPA concentration was treated as a continuous variable (odds ratio (OR): 1.24, 95% confidence interval (CI): 1.11-1.38, in model 3) or as tertiles (OR: 2.01, 95% CI: 1.49-2.72, between the lowest group and highest group, in model 3). This association was significant among male but not female participants. BPA also demonstrated a significant association with emphysema and chronic bronchitis in adults, particularly in males. No significant interaction was found for all the other subgroup analyses. Urinary BPA was associated with COPD-related diseases in adult participants, especially males.

The development of prediction model for cuffed tracheal tube size from the middle finger in pediatrics: a concise and feasible approach.

Background: Selecting the optimal tracheal tube size is critically important for pediatric patients. Age-based formulas are often used, but still have limitations. The aim of this prospective study was to investigate whether middle finger measurements correlate with cuffed tracheal tube size and to further develop a prediction model based on these measurements. Methods: Patients under 12 years of age scheduled for elective surgery involving tracheal intubation were enrolled in the study. The length was determined from the tip of the distal metacarpal to the palm's root on the palm side, while the circumference was measured at the base of the palm using a soft tape measure. The appropriate cuffed tracheal tube size was determined based on specific criteria. If the tube encountered resistance during insertion or required an airway pressure >25 cmH2O to detect an audible leak, it was replaced with a tube 0.5 mm smaller. Conversely, if an audible leak occurred at an airway pressure <10 cmH2O, or peak pressure >25 cmH2O, or the cuff pressure >25 cmH2O to achieve a seal, the tube was exchanged for one with a 0.5 mm larger. Linear regression analysis was used to examine the association between middle finger circumference and length with the cuffed tracheal tube size. Subsequently, regression equations were constructed based on the results of the linear regression analysis and their predictive performance was compared to the conventional age-based formulas, including the Khine formula and Motoyama formula. The predictive performance was evaluated by mean absolute error (MAE), root mean square error (RMSE), and prediction accuracy. Results: A total of 261 patients were analyzed in our study. The mean age of the patients was 46.19±35.83 months. The linear relationship was observed between the cuffed tracheal tube size and the middle finger circumference and middle finger length with R2 values of 0.77 and 0.73, respectively. In comparison to conventional age-based formulas, both middle finger circumference and middle finger length demonstrated superior predictive performance, characterized by lower MAE and RMSE, as well as higher prediction accuracy. Notably, the regression equation based on the middle finger circumference obtained the higher predictive accuracy of 0.590, with an MAE of 0.259 and an RMSE of 0.333 as opposed to the predictive accuracy of 0.391, MAE of 0.349, and RMSE of 0.473 derived from conventional age-based formulas. Based on the regression coefficients of linear regression, simplified formulas were proposed, with the middle finger circumference-based formula emerging as the most accurate and simple option. Conclusions: The appropriate cuffed tracheal tube size could be predicted by the middle finger circumference. Our proposed formula 'cuffed tracheal tube internal diameter (mm) = middle finger circumference (cm) - 0.2' has the potential to improve the selection of the cuffed tracheal tube size in pediatric patients.

Comparative study on alleviating effect of kiwi berry (Actinidia arguta) polysaccharide and polyphenol extracts on constipated mice.

Kiwi berry (Actinidia arguta) is beneficial for relieving constipation, but the mechanism of easing constipation is still unknown. The alleviating effects of kiwi berry polysaccharide and polyphenol extracts on loperamide induced constipation were studied. Administration with polysaccharide extract of kiwi berry in loperamide-induced constipation mice distinctly decreased the body weight gain by 124.0%, the number and the water content of feces was decreased by 152.4% and 107.0% respectively, gastrointestinal (GI) transit rate was decreased by 39.5% and the time to the first dark stool was largen by 56.2% as compared with those in the loperamide group, respectively. The levels of excitability neurotransmitters were increased, and the inhibitory neurotransmitter was decreased in the kiwi berry extracts groups compared with the loperamide group. The levels of aquaporins were decreased to ameliorate constipation. Moreover, kiwi berry extracts can protect colon smooth muscle cells from apoptosis and help to restore colon health. Interstitial cells of Cajal (ICC) and animal experiments suggested that kiwi berry extracts can up-regulate the expression levels of stem cell factors (SCF)/c-kit protein. Kiwi berry can remodel the structure of microbial communities. All findings suggest that kiwi berry polysaccharide and polyphenol especially its polysaccharide extract, can effectively alleviate constipation induced by loperamide. Kiwi berry is a promising food supplement that can be used to relieve constipation.

Nickel-Catalyzed Cross-Redistribution between Hydrosilanes and Silacyclobutanes.

Silanes are important in chemistry and material science. The self-redistribution of HSiCl3 is an industrial process to prepare SiH4 , which is widely used in electronics and automobile industries. However, selective silane cross-redistribution to prepare advanced silanes is challenging. We now report an enthalpy-driven silane cross-redistribution to access bis-silanes that contain two different types of Si-H bonds in the same molecule. Compared with entropy-driven reactions, the enthalpy-driven reaction shows high regioselectivity, broad substrate scope (62 examples) and high atom economy. Our combined experimental and computational study indicates that the reaction proceeds through a Ni0 -NiII -NiIV catalytic cycle.

Sustainable removal of soil arsenic by naturally-formed iron oxides on plastic tubes.

Arsenic (As) pollution in paddy fields is a major threat to rice safety. Existing As remediation techniques are costly, require external chemical addition and degrade soil properties. Here, we report the use of plastic tubes as a recyclable tool to precisely extract As from contaminated soils. Following insertion into flooded paddy soils, polyethylene tube walls were covered by thin but massive Fe coatings of 76.9-367 mg Fe m-2 in 2 weeks, which adsorbed significant amounts of As. The formation of tube-wall Fe oxides was driven by local Fe-oxidizing bacteria with oxygen produced by oxygenic phototrophs (e.g., Cyanobacteria) or diffused from air through the tube wall. The tubes with As-bound Fe oxides can be easily separated from soil and then washed and reused. We tested the As removal efficiency in a pot experiment to remove As from ~ 20 cm depth/40 kg soils in a 2-year experiment and achieved an overall removal efficiency of 152 mg As m-2 soil year-1, comparable to phytoremediation with the As hyperaccumulator Pteris vittata. The cost of Fe hooks was estimated at 8325 RMB ha-1 year-1, and the profit of growing rice (around 16080 RMB ha-1 year-1 can be still maintained. The As accumulated in rice tissues was markedly decreased in the treatment (>11.1 %). This work provides a low-cost and sustainable soil remediation method for the targeted removal of As from soils and a useful tool for the study and management of the biogeochemical Fe cycle in paddy soils.

A learning curve of a novel multimodal endotracheal intubation assistant device for novices in a simulated airway: a prospective manikin trial with cumulative sum method.

Background: Awake fiberoptic intubation is conventionally performed in anticipated difficult airways. However, obstruction by secretions and sputum makes it challenging for novices. A prototype of a novel multimodal endotracheal intubation assistant device (MEIAD) was developed for an indication of airway according to end-tidal carbon dioxide (ETCO2) and image. At the tip, 4 sampling tubes collected ETCO2 concentration. The airway direction is located according to an advanced algorithm based on 4 directions' concentrations. It assists awake intubation, especially with unclear view field. The objective was to analyze the learning curve of MEIAD for novices on a manikin by cumulative sum method (CUSUM) and evaluate the utility. Methods: A total of 16 novice residents with less than 2-year clinical experience were enrolled. After instruction, each individual exercised 40 insertions with MEIAD on a difficult airway simulation. Insertion success (defined as a visualization of the carina within 120 seconds), insertion time (the time from when the guiding scope entered the nasal cavity to the carina was visible), and self-confidence score (subjective score with a numerical rating scale from 0 to 10) were recorded. The acceptable and unacceptable failure rates of CUSUM were set as 15% and 30%, respectively. The exercises were divided into 2 phases (phase 1: 1-20, phase 2: 21-40) for further evaluation. All continuous data were expressed by median (IQR, interquartile ranges) and analyzed using Mann-Whitney test. All categorical variables were expressed as percentages and compared by the χ2 test. Results: Among the 16 residents, 15 were able to cross the lower decision boundary in an average of 21.27±9.51 attempts using the novel device. The insertion time [24.0 (17.0-42.0) vs. 17.5 (14.0-28.0) seconds, P<0.001] and success rate (88.4% vs. 97.5%, P<0.001) were improved with increased experience. The confidence score was significantly improved from 2.5 (1.3-4.0) to 7.0 (7.0-8.0). Conclusions: MEIAD showed a satisfactory learning curve and efficacy on the manikin for novices. However, as a small exploratory manikin trial, the results cannot be replicated in clinical practice. MEIAD is expected to be further improved and potential to be an alternative device for difficult airways.

Development and validation of a machine-learning model for prediction of hypoxemia after extubation in intensive care units.

Background: Extubation is the process of removing tracheal tubes so that patients maintain oxygenation while they start to breathe spontaneously. However, hypoxemia after extubation is an important issue for critical care doctors and is associated with patients' oxygenation, circulation, recovery, and incidence of postoperative complications. Accuracy and specificity of most related conventional models remain unsatisfactory. We conducted a predictive analysis based on a supervised machine-learning algorithm for the precise prediction of hypoxemia after extubation in intensive care units (ICUs). Methods: Data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database for patients over age 18 who underwent mechanical ventilation in the ICU. The primary outcome was hypoxemia after extubation, and it was defined as a partial pressure of oxygen <60 mmHg after extubation. Variables and individuals with missing values greater than 20% were excluded, and the remaining missing values were filled in using multiple imputation. The dataset was split into a training set (80%) and final test set (20%). All related clinical and laboratory variables were extracted, and logistics stepwise regression was performed to screen out the key features. Six different advanced machine-learning models, including logistics regression (LOG), random forest (RF), K-nearest neighbors (KNN), support-vector machine (SVM), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), were introduced for modelling. The best performance model in the first cross-validated dataset was further fine-tuned, and the final performance was assessed using the final test set. Results: A total of 14,777 patients were included in the study, and 1,864 of the patients' experienced hypoxemia after extubation. After training, the RF and LightGBM models were the strongest initial performers, and the area under the curve (AUC) using RF was 0.780 [95% confidence interval (CI), 0.755-0.805] and using LightGBM was 0.779 (95% CI, 0.752-0.806). The final AUC using RF was 0.792 (95% CI, 0.771-0.814) and using LightGBM was 0.792 (95% CI, 0.770-0.815). Conclusions: Our machine learning models have considerable potential for predicting hypoxemia after extubation, which help to reduce ICU morbidity and mortality.

Oscillatory rheotaxis of artificial swimmers in microchannels.

Biological microswimmers navigate upstream of an external flow with trajectories ranging from linear to spiralling and oscillatory. Such a rheotactic response primarily stems from the hydrodynamic interactions triggered by the complex shapes of the microswimmers, such as flagellar chirality. We show here that a self-propelling droplet exhibits oscillatory rheotaxis in a microchannel, despite its simple spherical geometry. Such behaviour has been previously unobserved in artificial swimmers. Comparing our experiments to a purely hydrodynamic theory model, we demonstrate that the oscillatory rheotaxis of the droplet is primarily governed by both the shear flow characteristics and the interaction of the finite-sized microswimmer with all four microchannel walls. The dynamics can be controlled by varying the external flow strength, even leading to the rheotactic trapping of the oscillating droplet. Our results provide a realistic understanding of the behaviour of active particles navigating in confined microflows relevant in many biotechnology applications.

ngsJulia: population genetic analysis of next-generation DNA sequencing data with Julia language.

A sound analysis of DNA sequencing data is important to extract meaningful information and infer quantities of interest. Sequencing and mapping errors coupled with low and variable coverage hamper the identification of genotypes and variants and the estimation of population genetic parameters. Methods and implementations to estimate population genetic parameters from sequencing data available nowadays either are suitable for the analysis of genomes from model organisms only, require moderate sequencing coverage, or are not easily adaptable to specific applications. To address these issues, we introduce ngsJulia, a collection of templates and functions in Julia language to process short-read sequencing data for population genetic analysis. We further describe two implementations, ngsPool and ngsPloidy, for the analysis of pooled sequencing data and polyploid genomes, respectively. Through simulations, we illustrate the performance of estimating various population genetic parameters using these implementations, using both established and novel statistical methods. These results inform on optimal experimental design and demonstrate the applicability of methods in ngsJulia to estimate parameters of interest even from low coverage sequencing data. ngsJulia provide users with a flexible and efficient framework for ad hoc analysis of sequencing data.ngsJulia is available from: https://github.com/mfumagalli/ngsJulia.