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  • Minimum required distance for clinically significant measurement of habitual gait speed | BMC Geriatrics

    Minimum required distance for clinically significant measurement of habitual gait speed | BMC Geriatrics

    Participants

    Twenty-four healthy, community-dwelling older adults, consisting of 15 men and 9 women with a mean age of 72.1 ± 4.1 years, participated (Table 1). The eligibility criteria of this study were as follows: age ≥ 65 years; ability to walk independently without assistive devices; and absence of conditions that could significantly influence gait, such as neurological disorders (e.g., Alzheimer’s disease, Parkinson’s disease, or stroke), severe cardiovascular or respiratory impairments with symptoms during daily activities (e.g., heart failure, chronic obstructive pulmonary disease), or musculoskeletal problem that disable independent gait (e.g., joint replacement, spinal surgery, or advanced arthritis).

    Table 1 Baseline characteristics of study participants

    Sample size calculation

    The required sample size was determined based on the population within-subject standard deviation (PWSD). The number of subjects was determined to estimate PWSD within 10% of the population value ((frac{1.96}{sqrt{2nleft(m-1right)}}leq0.1,;m=the;number;of;observations;per;subject)) using the variance of PSWD ((frac{{sigma }_{w}}{sqrt{2nleft(m-1right)}}, {sigma }_{w}=PWSD)) [21]. A sample size of 24 was required for all of the distances with nine or more observations per subject (m ≥ 9) except for the two longest distances (4.9 and 5-m).

    Muscle mass and strength assessments

    Participants underwent bioimpedance analysis using an InBody S10 device (InBody Co., Ltd., Seoul, South Korea) to determine height-adjusted appendicular skeletal muscle mass. Muscle strength was assessed by measuring handgrip and isometric knee extension strength. Handgrip strength was measured using a Takei 5401 Digital Dynamometer (Takei Scientific Instruments Co., Ltd., Niigata, Japan) in a standing position with the elbow fully extended. Isometric knee extension strength was evaluated using a TKK-5710e tension meter (Takei Scientific Instruments Co., Ltd., Niigata, Japan); during measurement, participants were seated on a chair with a dynamometer anchored to it, maintaining knee flexion at 90°. Both measurements were conducted bilaterally, with each side assessed twice and a 1-min rest period between attempts. Participants were instructed to exert maximum effort for each measurement, and the highest reading was used in the analysis. All procedures were conducted by a single trained assessor following the recommendations of Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People [9, 10].

    Physical performance assessments

    Physical performance was evaluated using the Short Physical Performance Battery (SPPB) [22], the 30-s chair stand test [23], the five-times sit-to-stand test [24], and the timed up-and-go test [25]. All assessments were conducted by a single trained assessor in a spacious setting under consistent environmental conditions, following the protocols of the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People [9, 10].

    10-m gait speed test and data acquisition

    Participants walked along a 10-m walkway, which included a 2-m acceleration zone for a dynamic start and a 2-m deceleration zone at the end. They were instructed to walk at their usual pace on a hard surface while wearing comfortable footwear. The 10-m walk was repeated three times, with a minimum rest period of 2 min between trials. Recordings were captured using an Apple iPad Pro 11 2nd Generation (Apple, Inc., Cupertino, CA, USA) equipped with RGB cameras arranged perpendicularly to the walking path at a distance of 3.8 m and a height of 0.8 m. Videos were recorded in the sagittal plane (resolution: 800 × 600 pixels; 30 fps; Fig. 1).

    Fig. 1

    Overview of the experimental set-up. a Schematic diagram showing the measurement zones and camera position. b Photograph of the setup

    Gait analysis using 2D pose estimation

    A customized pose estimation model (ViFive, Inc., Boulder, CO, USA) was used, which tracked 14 key body points using an architecture adapted from a standard stacked hourglass model [26]. We introduced multiple objectives to enhance the context, accuracy, speed, and stability of the model, which are vital for musculoskeletal assessment. The classification model included a random forest classifier with optimized features to increase accuracy and speed while reducing the model size. Pixel-per-meter estimation used markers at 2 and 8 m (Fig. 1). The CoM of each subject was determined using the weighted sums of the body segment centers of mass (Fig. 2a).

    Fig. 2
    figure 2

    Illustrative case. a The movement pattern of the center of mass over time as estimated via pose estimation. b Gait speed of each segment according to the measurement distance (1.0–5.0 m). The x-axis represents the percentile of total walking distance (%), and the y-axis represents gait speed (m/s). c Distribution of gait speed according to the measurement distance

    Gait speed estimation

    Gait speed was measured using two independent methods for validation: manually with a stopwatch and using pose estimation algorithms. Manually assessed speed was determined by an evaluator using a stopwatch to record the time taken for the subjects to pass by the markers set at 2 and 8 m. Pose estimation gait speed was calculated by dividing the distance covered between frames by the elapsed time using either the CoM or the leading foot as reference points. CoM-referenced measurements simulate those obtained via conventional motion capture system, whereas leading foot-referenced measurements simulate those made using walkway or pressure sensors such as GAITRite® (CIR Systems Inc., Franklin, NJ, USA).

    Gait speed measurement validation

    Gait speeds measured using a stopwatch and pose estimation were compared using a linear mixed-effects model, with speed over 6 (manual) or 5 m (pose estimation) per trial as the dependent variable and with subject random effect to account for multiple tests from each subject. The intraclass correlation coefficient (ICC) was used to evaluate absolute agreement between gait speed measurements obtained via the two methods for the same walking trials.

    Change of uncertainty with measured distance

    A 5-m walk video of a skeleton with 14 key points was extracted from each recording using our pose estimation algorithm. This was further edited by cropping at 0.1-m intervals to generate 4.9- to 1.0-m segments. One 5.0-m walk video generated two 4.9-m segments, three 4.8-m segments, and so forth, up to 41 segments for a 1.0-m walk, culminating in 861 segments of varying distance (Fig. 2b,c).

    The variability of gait speed across the measured distances was defined as the within-subject standard deviation (WSD) for each measured distance, calculated as the square root of the mean-square error in a one-way analysis of variance, where groups combined subjects with distance intervals. Three gait speed data from three measurements were collected for each group to avoid underestimating within-subject variation due to overlapping distances when distance intervals are not considered. For example, for a 4.7-m walk, four gait speed measurements were obtained at 4.7-m distances (0–4.7, 0.1–4.8, 0.2–4.9, and 0.3–5.0 m), and within-subject variation at a 4.7-m distance was estimated by considering different distance intervals.

    Determination of minimum required distance

    To determine the minimum required distance, we utilized WSD at each measured distance. Given that confidence intervals (CI) quantify variability, we computed the half-width of the CI using WSD and the critical value corresponding to the chosen confidence level. Specifically, the 95% CI was calculated as 1.96 × WSD, and the 90% CI as 1.64 × WSD. For the measurement to be clinically meaningful, the half-width of the CI, reflecting gait speed variability, had to remain below the MCID of 0.1 m/s [27, 28]. Thus, the minimum required distance was defined as the shortest distance at which this criterion was met, ensuring that gait speed measurements remained within an acceptable range of variability.

    Factors affecting gait speed variability

    CoM trajectory was plotted as distance against time for each test. Linear regression analysis provided a trend line and the mean squared error (MSE) for each subject. As MSE quantifies deviations from the trend line, lower MSE values indicate less variability in gait speed, leading to a shorter minimum required distance. We investigated whether epidemiological, anthropometric, or clinical variables were associated with MSE using linear regression following Pearson’s correlation for continuous variables and point-biserial correlation for dichotomous variables to identify subject characteristics influencing the minimum required distance. All processing and statistical analyses were conducted using MATLAB R2023b (MathWorks, Natick, MA, USA) and SAS 9.4 (SAS Institute, Cary, NC, USA), with statistical significance set at p < 0.05.

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  • How to create and edit custom passes

    How to create and edit custom passes

    Google Wallet is more than Google’s tap-to-pay app. Over the years, Wallet has expanded into a sort of all-in-one digital document manager for anything and everything you might keep in a real wallet — transit passes, event tickets, store loyalty cards, and more.

    Last August, Wallet got support to create custom passes for pretty much anything, and more recently, Google rolled out the ability to edit those passes without having to completely recreate them from scratch. If you haven’t interacted with this Wallet’s custom pass functionality much, there’s quite a bit to wrap your head around. Here’s everything you need to know.

    What is a custom pass?

    Google Wallet’s got bespoke onboarding for payment cards, transit passes, loyalty cards, gift cards, and IDs. For anything else, you can use an Everything else option to create a custom pass.

    When you add a pass through this method, Wallet will do its best to automatically detect the type of document you’re uploading to give the resulting digital pass relevant artwork. It can detect event tickets, insurance cards of multiple types, loyalty cards, student IDs, business cards, and more. Any document that doesn’t fall into one of Wallet’s predefined buckets will be added as “Other.”

    Related

    12 things to add to Google Wallet that aren’t your credit card

    Use Google Wallet for more than payments

    How to create a custom pass

    Creating a custom pass only takes a few steps, and Google Wallet does most of the work for you. The main thing you have to do manually is scan the document using your phone’s camera. Here’s how it works.

    1. Open the Google Wallet app.
    2. Tap the Add to Wallet button in the lower right corner.

      The Google Wallet interface with a red arrow pointing to 'Add to Wallet'

    3. Tap Everything else.

      The Google Wallet interface with a red box around 'Everything else'

    4. Line your document up in the viewfinder and tap the capture button.
    5. On the next screen, you can crop, rotate, or retake the photo. If what you got looks good, tap Done.

      The Google Wallet interface, showing a censored insurance card

    6. Wallet will take a moment to process, then show the resulting pass.
    7. Verify the info on your custom pass is correct. If it’s right, tap Add. If it’s incomplete or inaccurate, tap Edit.

      The Google Wallet interface showing a custom pass being added

    Additional information fields added in the Edit view in step 7 above aren’t displayed on the custom pass graphic. To view any information added manually, tap the three-dot icon in the top right corner when viewing your pass.

    How to edit a custom pass

    Google just recently introduced the option to edit custom passes after adding them to Wallet, saving you the hassle of reuploading a pass if you spot an error or omission. Here’s how to do that.

    1. Open the Google Wallet app.
    2. Tap the pass you want to edit.

      The Google Wallet interface with a red rectangle around a custom car insurance card

    3. Tap the three-dot icon in the upper right corner.

      The Google Wallet interface with a red arrow pointing to the overflow menu icon for a custom pass

    4. Scroll down and tap Edit.

      The Google Wallet interface with a red rectangle around the edit button for a custom pass

    5. Make your changes, then tap Save.

      The Google Wallet interface with a red rectangle around the Save button on the Edit pass info screen

    You’re also able to add additional information fields in the edit view, in case the initial upload missed a detail like your vehicle identification number on a car insurance card.

    A surface with the Google Wallet logo next to the Samsung Wallet logo, surrounded by several credit cards.

    Related

    Google Wallet vs. Samsung Wallet: Which is better?

    Which digital wallet should you be using?

    An easy way to digitize all your docs

    Google Wallet’s custom pass functionality makes the app infinitely more useful, and Google’s recent decision to allow users to edit documents after uploading them makes it even more convenient still. It’s a great way to keep documents you might occasionally need at hand without actually needing to carry around all that paper.

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  • Move over microbiome, time for the human gut’s “virome” to shine

    Move over microbiome, time for the human gut’s “virome” to shine

    For years, bacteria dominated gut health research. Now, the gut virome is gaining attention as a major player in health and disease. Bacteriophages, which are viruses that infect bacteria, make up around 90% of the gut virome.

    Though small in biomass, they outnumber bacteria by up to tenfold. These tiny viruses shape microbial communities, influence immunity, and affect gut health.


    A landmark review published recently in Precision Clinical Medicine reveals how the gut virome links to diseases like inflammatory bowel disease (IBD), colorectal cancer, and Clostridium difficile infection (CDI).

    Gut’s virome changes across life stages

    The gut virome changes constantly throughout life. Infants show high diversity in gut bacteriophages (also called phages), which is shaped by birth method, diet, and antibiotic exposure.

    As individuals grow, diet and hormones refine the virome. In adults, phages and bacteria form a stable, balanced community.

    However, aging shifts this balance. Older adults show more lysogenic phages, which integrate into bacterial genomes and potentially alter metabolism and immune interactions.

    Diet and environment shape the virome

    Diet greatly influences the virome. High-fiber diets support beneficial phages by encouraging helpful bacteria. Western diets, rich in fat and sugar, promote harmful phages.

    Urbanization reduces exposure to natural viruses. Studies show that rural diets which are rich in fiber boost gut virome diversity.

    Host genetics and immunity also play roles. Genetic variants can affect viral detection and clearance. Immune defenses, like interferons and IgA, keep the virome balanced.

    However, immune dysfunction can trigger viral imbalances, worsening conditions like HIV and gut inflammation.

    Viruses and bacteria interacting

    Viruses, including phages, along with bacteria and fungi form a complex and dynamic ecosystem in the gut. The components interact in positive and negative ways, thus affecting host metabolism, immune regulation and resistance to disease.

    The gut virome plays a crucial regulatory role in these intricate interactions. Phages interact with bacteria through lytic, lysogenic, and budding cycles, which regulate bacterial populations and gene flow.

    In a form of microbial arms race, the bacteria defend against phages using CRISPR systems and the phages evolve escape mechanisms.

    Some phages even boost bacterial metabolism and biofilm formation, affecting disease risk. For instance, phages can transfer genes that enhance bacterial survival in acidic conditions.

    Virome’s influence on immunity

    The virome affects gut immunity deeply. Phages can anchor to gut mucus and form a protective barrier. They also shape our own T and B cell activity and regulate macrophages. In addition, viruses that infect eukaryotic cells affect immune pathways and maintain gut balance.

    This infographic illustrates four major therapeutic approaches—fecal microbial transplantation (FMT), phage therapy, dietary interventions, and probiotics/prebiotics—that aim to restore gut health by modulating the microbiome and virome. Each strategy offers unique methods, benefits, and challenges in managing gastrointestinal disorders such as IBD, CRC, and CDI, highlighting the growing potential of virome-informed precision medicine. Credit: Precision Clinical Medicine
    This infographic illustrates four major therapeutic approaches—fecal microbial transplantation (FMT), phage therapy, dietary interventions, and probiotics/prebiotics—that aim to restore gut health by modulating the microbiome and virome. Each strategy offers unique methods, benefits, and challenges in managing gastrointestinal disorders such as IBD, CRC, and CDI, highlighting the growing potential of virome-informed precision medicine. Click image to enlarge. Credit: Precision Clinical Medicine

    However, infections and antibiotics can disrupt this harmony and lead to inflammation. Phages can trigger TLR9 pathways, causing excessive immune responses such as those linked to IBD.

    Virome’s role in disease

    Imbalances in the gut virome have been linked to several gut diseases. In IBD, specific phages become abundant and worsen inflammation.

    Certain groups of phages (such as Caudovirales) amplify immune responses, while norovirus and rotavirus can damage the gut lining. Viral imbalances are also common in IBS and CDI.

    In colorectal cancer, phages and eukaryotic viruses like HPV and JC virus (polyomavirus) appear more often. They may promote tumor growth by altering bacterial communities and gene expression.

    Studies suggest that some phages directly influence cancer risk by promoting biofilms and transferring harmful genes.

    Virus-based treatments

    Several therapies now explore the virome’s potential to treat certain diseases or conditions. Fecal microbiota transplantation (FMT) restores gut balance and reduces inflammation in IBD and CDI.

    FMT works not only by shifting bacteria but also by transferring beneficial phages. Studies show that donor phages often align quickly with recipients and promote recovery.

    Phage therapy, which uses viruses to kill specific bacteria, is another approach that is gaining traction. It can reduce harmful microbes while preserving beneficial ones.

    Researchers have created phage cocktails that target specific gut pathogens like E. coli and Klebsiella pneumoniae, and this approach has had promising results in animal models.

    Dietary strategies also reshape the virome. High-fiber diets boost beneficial phages and support bacterial diversity.

    Whey protein has shown potential in managing Crohn’s disease by improving phage-bacteria interactions.

    Other interventions, such as exclusive enteral nutrition and low-FODMAP diets, also show benefits in gut diseases.

    Probiotics, prebiotics, and phages

    Probiotics introduce beneficial bacteria, while prebiotics feed them. Combining them, known as symbiotics, shows promise for restoring and maintaining gut health.

    Recent research suggests that adding phages can enhance these effects. Phage-based products, such as PreforPro, have already shown benefits in clinical trials.

    These products can reduce populations of harmful bacteria and improve probiotic performance, thereby creating a more stable gut environment.

    Using gut viruses to detect diseases early

    The gut virome is now being studied as a diagnostic tool. Viral patterns are more stable than bacterial ones, making them reliable biomarkers.

    Distinct virome signatures can predict IBD and colorectal cancer. Machine learning models already use virome data to detect these diseases early.

    Virome profiling may also track treatment responses, such as FMT success in IBD and CDI.

    Challenges and future prospects

    Despite the excitement over potential new treatments, many hurdles remain. Current methods struggle to capture the full virome due to technical limits.

    Many phages are still unculturable, and their roles remain unclear. Researchers are working to improve viral databases and develop targeted therapies. Once these gaps close, virome-based therapies could change how we treat gut diseases.

    The study is published in the journal Precision Clinical Medicine.

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  • Development and validation of a risk prediction model for acute biliar

    Development and validation of a risk prediction model for acute biliar

    Introduction

    The onset of acute pancreatitis is primarily attributed to biliary system stones and alcohol consumption.1 Among these, acute biliary pancreatitis (ABP) is a severe inflammatory condition of the pancreas induced by biliary stones. Epidemiological data suggest that the mortality rate in ABP patients ranges from 20% to 40%, indicating considerable variability in disease progression.2 Biliary stones not only serve as a major trigger for acute pancreatitis but also significantly influence treatment outcomes and the prognosis of ABP.3 Therefore, treatment strategies for ABP should encompass both the removal of the underlying cause and the management of the inflammatory response, aiming to reduce recurrence risk and improve overall survival rates.

    For patients experiencing their first episode of acute biliary pancreatitis (ABP), treatment options may include conservative management, surgical intervention, or interventional therapy.4 Clinical studies have shown that gallstones are a major factor contributing to ABP recurrence; as a result, cholecystectomy is widely regarded as an effective approach to reduce recurrence rates.5,6 Laparoscopic cholecystectomy (LC), considered the “gold standard” for treating gallstones, has become the preferred treatment due to its minimally invasive nature, quicker recovery, and shorter hospital stays.7 While LC has yielded favorable outcomes in the treatment of gallstones, certain postoperative complications, including acute pancreatitis, may still arise. When biliary system stones induce pancreatitis, it leads to ABP, which not only exacerbates postoperative discomfort but also prolongs hospital stays, diminishes the overall benefits of surgery, and, in severe cases, increases the risk of mortality.8 Furthermore, given the complexity of treating pancreatitis, its often-prolonged course, and its association with a relatively poor prognosis, early prediction of the risk of pancreatitis following LC in patients with gallstones is crucial.9 Timely and effective interventions to mitigate this risk represent an important area of research aimed at reducing the incidence of postoperative pancreatitis and improving patient outcomes.

    This study aims to develop and validate a predictive model for assessing the risk of post-laparoscopic cholecystectomy (LC) pancreatitis in patients with gallstones, utilizing demographic and clinical characteristics. By identifying key risk factors and providing a reliable risk assessment tool, our findings contribute to the advancement of early prevention strategies and the optimization of clinical management for gallstone-related ABP.

    Methods

    Study Population

    This study was designed as a retrospective cohort study, collecting demographic data and clinical characteristics of patients who underwent laparoscopic cholecystectomy at Henan Province Hospital of Traditional Chinese Medicine from June 2021 to December 2023. This dataset was considered as training set (n=871). We then collected the patient’s data from March 2024 to October 2024 at the same hospital, and this dataset was considered as external validation set (n=160).

    The inclusion criteria are as follows: (1) Patients diagnosed with gallstones according to the Chinese Consensus on the Diagnosis and Treatment of Chronic Cholecystitis and Gallstones (2018),10 confirmed by ultrasound, magnetic resonance imaging (MRI), or abdominal CT; (2) No history of jaundice; (3) First-time laparoscopic cholecystectomy treatment. The following patients were excluded: (1) Age <18 years; (2) History of pancreatic diseases, such as acute pancreatitis (AP), chronic pancreatitis, or pancreatic cancer; (3) Presence of obstructive cholecystitis or acute cholecystitis; (4) Severe dysfunction of vital organs, including the heart, liver, or kidneys; (5) Severe coagulation disorders or bleeding disorders; (6) History of malignancies; (7) Presence of infectious diseases or systemic inflammatory response syndrome; (8) Women in special physiological stages, such as pregnancy or lactation; (9) Recent use of antibiotics, nonsteroidal anti-inflammatory drugs (NSAIDs), glucocorticoids, or other immunosuppressants; (10) Incomplete clinical data. Finally, 968 patients were included in the study.

    Laparoscopic Cholecystectomy

    Briefly, the laparoscopic cholecystectomy surgical procedure is as follows: Preoperative routine disinfection and draping are performed. After satisfactory anesthesia, the patient is positioned in a head-up, foot-down position with a left tilt of approximately 20°C. Pneumoperitoneum is established, maintaining an intra-abdominal pressure of 8–12 mmHg. The four-port technique is used to enter the abdomen, and laparoscopy is performed to explore the abdominal cavity, confirm the presence of gallstones, and assess the morphology, size, and surrounding structures of the gallbladder. Normal tissues and organs are carefully separated. The cystic artery and cystic duct are clipped with titanium clips and then severed. Hemostasis is achieved through electrocautery, and the gallbladder is removed using a sterile glove. Postoperatively, patients receive routine fluid replacement, anti-infective therapy, and nutritional support.

    Diagnosis of Acute Biliary Pancreatitis

    According to the Chinese Guidelines for the Diagnosis and Treatment of Acute Pancreatitis (2021),11 a diagnosis of ABP can be made if any two of the following three criteria are met at one month after operation: (1) sudden onset of upper abdominal pain (persistent and severe, often radiating to the back); (2) serum amylase and/or lipase levels ≥ three times the upper limit of normal; (3) typical imaging findings of acute pancreatitis. ABP refers to acute pancreatitis patients in whom biliary stones have been confirmed by examinations such as ultrasound, computed Tomography, magnetic resonance cholangiopancreatography, or endoscopic retrograde cholangiopancreatography.

    Data Collection and Definition

    The collected data included demographic information and clinical characteristics: age, sex, body mass index (BMI) is equal to weight (kg) divided by the square of height (m), smoking is defined as someone who has smoked continuously or cumulatively for six months or more in their lifetime,12 alcohol consumption was defined as drinking at least once per week during the past year, duration of disease,13 diabetes: fasting plasma glucose (FPG) ≥7.0 mmol/L or 2-hour plasma glucose ≥11.1 mmol/L during an oral glucose tolerance test or HbA1c ≥ 6.5% (48 mmol/mol),14 hypertension: systolic blood pressure ≥140 mmHg and/or diastolic blood pressure≥90 mmHg,15 hyperlipidemia (total Cholesterol (TC)≥5.2 mmol/L or low-density lipoprotein cholesterol≥3.4 mmol/L or high-density lipoprotein cholesterol < (1.0 mmol/L in men or <50 1.3 mmol/L in women or triglycerides≥1.7 mmol/L),16 and choledocholithiasis. The following biochemical data were collected: alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, TG, TC, total protein, albumin, FBG, blood urea nitrogen, creatinine, C-reactive protein (CRP), white blood cell (WBC), hemoglobin, Hematocrit (HCT), mean corpuscular volume, red cell distribution width (RDW), neutrophil, monocyte, lymphocyte, platelet.

    The clinical characteristics: gallbladder size (determined by ultrasound), gallbladder wall thickness (determined by B-mode ultrasound), stone diameter, number of stones (single, >3 stones, determined by ultrasound), stone characteristics (determined by MRCP or MRI), history of pancreatic disease, choledocholithiasis (confirmed by MRCP and endoscopic ultrasound), operation time, intraoperative blood loss, time to pain relief, duration of hospitalization, and number of intubations, somatostatin usage, incisional infection, timing of cholecystectomy (early: within 14 days, delayed: more than 14 days).2

    Statistical Analysis

    In this study, multiple measures were implemented to control potential biases inherent in retrospective research. To ensure data quality, a dual-entry process was conducted independently by two researchers, followed by third-party verification. Outcome assessments were performed in a blinded manner, and strict adherence to predefined inclusion and exclusion criteria was maintained. Regarding data completeness, multiple imputations were applied using the “mice” package to handle missing values, and variables with a missing rate exceeding 10% were excluded from the analysis.

    Statistical analyses were conducted using IBM SPSS 23.0 and R 4.4.0. Categorical variables were expressed as frequencies (percentages), and group comparisons were performed using the chi-square (χ²) test. Continuous variables were presented as mean ± standard deviation (for normally distributed data, analyzed using the independent samples t-test) or median [interquartile range] (for non-normally distributed data, analyzed using the Wilcoxon rank-sum test). Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for acute biliary pancreatitis (ABP), with odds ratios (ORs) and 95% confidence intervals (CIs) calculated. Based on the least absolute shrinkage and selection operator (LASSO) and multivariate regression results, a nomogram model was developed to facilitate individualized risk prediction. Internal validation was conducted using a five-fold cross-validation approach, while external validation was performed using datasets from different time periods.

    The predictive performance of the model was assessed using a comprehensive evaluation framework. Discriminative ability was quantified by the concordance statistic (C-statistic) based on the area under the receiver operating characteristic (ROC) curve. The SHAP value was used for evaluating the importance of features. Calibration was evaluated using calibration curves to assess the agreement between predicted and observed outcomes. The clinical utility of the model was determined through decision curve analysis (DCA). All statistical tests were two-tailed, with a significance threshold set at P < 0.05.

    Results

    Baseline Characteristics for Training and Validation Set

    Based on the inclusion and exclusion criteria, we identified a total of 871 patients in the training set and 97 patients in the validation set who underwent laparoscopic cholecystectomy. The incidences of acute biliary pancreatitis (ABP) were 9.07% and 8.75%, respectively. No significant differences were observed in the ABP incidences between the training set and validation set (P = 0.897). The mean age of the training set was 54.27 ± 8.17 years, with 45.01% of patients being female. Among all patients, 19.8% had a history of alcohol consumption, and 36.97% had a history of smoking. The prevalence of hypertension, diabetes, and hyperlipidemia was 33.52%, 24.57%, and 33.64%, respectively. The mean age of the validation set was 54.98 ± 8.45 years, with 38.75% of patients being female. The proportions of patients with a history of smoking and drinking were slightly higher in the validation set, but no significant differences were found. The rates of hypertension, diabetes, and hyperlipidemia exhibited similar trends in both sets. There were no significant differences in demographic characteristics, clinical features, treatment factors, or laboratory results between the training and validation sets (P > 0.05). Detailed results for both groups can be found in Table 1.

    Table 1 General Characteristics of Training and Validation Set

    Baseline Characteristics Between ABP and Non-ABP in Training Set

    Our results indicate that there were no significant differences between the ABP and non-ABP groups in terms of age (P = 0.238), sex (P = 0.292), BMI (P = 0.572), smoking status (P = 0.304), drinking (P = 0.103), hypertension (P = 0.897), diabetes (P = 0.872), or disease duration (P = 0.067). However, the prevalence of hyperlipidemia was significantly higher in the ABP group (44.30%) compared to the non-ABP group (32.58%) (P = 0.035). Additionally, the baseline APACHE II score was significantly higher in the ABP group than in the non-ABP group (P < 0.001). Regarding clinical characteristics, the prevalence of choledocholithiasis was significantly higher in the ABP group than in the non-ABP group (P = 0.004). No significant differences were observed in gallbladder wall thickness, diameter, size, number, or shape (P > 0.05). During the operation, there were no significant differences in operation time, intraoperative blood loss, or contrast imaging times between the ABP and non-ABP groups (P > 0.05). However, the number of intubation attempts was significantly higher in the ABP group than in the non-ABP group (P < 0.001). No significant differences were found in time to pain relief, duration of hospitalization, rates of balloon dilation or somatostatin use, or the incidence of incisional infections (P > 0.05). The ABP group tended to have a delayed timing of cholecystectomy compared to the non-ABP group (P < 0.001). Biochemical parameters revealed that the ABP group had higher levels of triglycerides (TG), C-reactive protein (CRP), white blood cells (WBC), red cell distribution width (RDW), and neutrophils compared to the non-ABP group (P < 0.05). There were no significant differences in other biochemical parameters between the two groups (P > 0.05). Detailed data for both groups are presented in Table 2.

    Table 2 Comparisons of Clinical Characteristics Between ABP and Non-ABP in Training Set

    Developing of Model Predicting ABP in the Training Set

    Univariate logistic regression analysis revealed that hyperlipidemia, baseline APACHE II score, choledocholithiasis, number of intubation attempts, timing of cholecystectomy, levels of D-Dimer, triglycerides (TG), C-reactive protein (CRP), white blood cells (WBC), neutrophils, and red cell distribution width (RDW) were significantly associated with the occurrence of acute biliary pancreatitis (ABP) (P < 0.001). To refine the model, a LASSO regression was performed prior to the multivariate logistic regression (Figure 1A and B). In the final multivariate logistic regression model, ten variables were identified as significant predictors of ABP: baseline APACHE II (OR: 1.30, 95% CI: 1.10–1.52, P < 0.001), choledocholithiasis (OR: 2.49, 95% CI: 1.25–4.95, P = 0.010), number of intubation attempts (OR: 3.17, 95% CI: 1.70–59.1, P < 0.001), timing of cholecystectomy (OR: 3.17, 95% CI: 1.63–6.15, P < 0.001), D-Dimer (OR: 1.99, 95% CI: 1.02–3.85, P = 0.042), TG (OR: 1.21, 95% CI: 1.06–1.37, P = 0.003), CRP (OR: 1.06, 95% CI: 1.04–1.08, P < 0.001), WBC (OR: 1.62, 95% CI: 1.37–1.93, P < 0.001), neutrophils (OR: 1.91, 95% CI: 1.01–3.61, P = 0.047), and RDW (OR: 1.24, 95% CI: 1.12–1.37, P < 0.001). Further details are presented in Table 3. We also performed the ROC analysis using these variables. The results were presented in the Supplementary material 1. The results suggested that the AUCs were 0.617 for APACHE II, 0.585 for choledocholithiasis, 0.620 for times of intubations, 0.617 for timing of cholecystector, 0.613 for TG, 0.750 for WBC, 0.845 for CRP, 0.619 for neutrophil, 0.654 for RDW and 0.554 for D-dimer.

    Table 3 Univariate and Multivariate Logistic Regression for ABP in the Training Set

    Figure 1 Development and validation of the predict model for ABP after LC. (A and B) LASSO regression identified the relevant risk factors. (C) Receiver operating characteristics curve (ROC) of predict model in training set. (D) ROCs of five samples using five-fold cross validation. (E) ROC of predicting model in external validation set. (F) SHAP analyses identified the importance of features in the model.

    Validation and Assessment of Model Predicting ABP

    The predictive ability of the established model was assessed using the training set. The model’s ROC curve in the training set was 0.949 (95% CI: 0.930–0.969, Figure 1C), indicating a relatively high predictive capability. We then performed internal validation using 5-fold cross-validation, which demonstrated high and stable predictability across the five random samples. The ROC values for folds 1–5 ranged from 0.855 to 0.962 (Figure 1D). In the external validation set, the ROC value was 0.924 (95% CI: 0.874–0.973, Figure 1E). SHAP analysis revealed that CRP had the highest feature importance, followed by WBC, RDW, timing of cholecystectomy, and baseline APACHE II. D-Dimer ranked last in importance (Figure 1F). Based on these variables, we developed an individualized risk scoring system (Figure 2A).

    Figure 2 Assessment of predicting model for ABP. (A) Nomogram using identified risk factors for ABP after LC. (B and C) Calibration plots of predicting model in training and validation sets. (D and E) Unoptimized decision curves of training and validation sets. (F and G) Optimized decision curves of training and validation sets.

    Calibration analyses were performed for both the training and validation sets. The training set showed stable prediction performance for ABP (Figure 2B). Although the validation set exhibited some fluctuations, it remained stable with a predicted probability greater than 0.35 (Figure 2C). Decision curve analysis (DCA) further demonstrated that the model provided high net benefit across a range of threshold probabilities in both the training and validation sets (Figure 2D and E). The optimized DCA yielded similar results (Figure 2F and G). A threshold effect analysis revealed a significant dose-response relationship between the risk score and ABP occurrence. Specifically, for risk scores <0.032, the association was marginally significant (P = 0.035), while for risk scores ≥0.032, the association was highly significant (P < 0.001) (Figure 3).

    Figure 3 Dose-response between risk score and ABP in training set.

    Discussion

    Laparoscopic cholecystectomy (LC) is considered the “gold standard” for treating gallstones, as it effectively alleviates the patient’s condition. However, LC necessitates gallbladder removal, involves a certain degree of surgical trauma, and still carries a relatively high risk of postoperative complications. Among these, acute biliary pancreatitis (ABP) is one of the most common and severe, often manifesting with multiple symptoms that can compromise surgical outcomes and prolong hospital stays. Currently, no effective drugs are available for the treatment or prevention of pancreatitis. Previous studies have reported that the incidence of post-LC pancreatitis in gallstone patients ranges from approximately 2% to 9%.17,18 In this study, the incidence of postoperative pancreatitis was 9.07%, consistent with previous findings. ABP can present with symptoms such as fever, nausea, vomiting, and abdominal pain; in severe cases, it may lead to respiratory distress, shock, or even sudden death. Although systematic treatment can alleviate primary symptoms, pancreatitis still impacts overall therapeutic outcomes, underscoring the importance of early prevention.

    To address this, we developed a logistic regression-based predictive model using diverse clinical and laboratory parameters, with thorough validation to ensure reliability. Univariate analysis identified significant risk factors for ABP, including hyperlipidemia, APACHE II score, choledocholithiasis, intubation, cholecystectomy timing, and inflammatory markers (D-dimer, TG, CRP, WBC, neutrophils, RDW). LASSO regression was applied to prevent overfitting, yielding ten key predictors for the final multivariate model. These combined clinical and biochemical variables demonstrated strong predictive performance, with an AUC of 0.949 in the training set and 0.924 in external validation. Five-fold cross-validation (AUC: 0.855–0.962) confirmed model stability. SHAP analysis highlighted CRP, WBC, RDW, cholecystectomy timing, and APACHE II score as top contributors, underscoring the importance of inflammation and disease severity. Threshold effect and decision curve analyses further supported the model’s clinical utility. Despite minor calibration fluctuations, overall performance was consistent, affirming its robustness.

    Among the identified risk factors, the APACHE II score was significantly associated with ABP occurrence. Although the APACHE II score primarily reflects systemic physiological changes rather than localized disease status, it is widely regarded as an effective early diagnostic and prognostic tool for pancreatitis.19,20 Our statistical analysis showed that the APACHE II score was significantly higher in the ABP group than in the non-ABP group. Moreover, ROC analysis suggested that the APACHE II score could help differentiate ABP from non-ABP cases, highlighting the need for comprehensive assessments in LC patients to improve ABP prediction. Choledocholithiasis also emerged as a critical risk factor for ABP after LC. When gallstones are present in the common bile duct, they can cause obstruction, impair bile drainage, and lead to bile reflux into the pancreatic duct. This process can activate pancreatic enzymes such as trypsin, chymotrypsin, and elastase, triggering pancreatitis.21 Additionally, the increased bile duct pressure resulting from obstruction further exacerbates bile reflux into the pancreatic duct, worsening pancreatic injury.22 The number of intubations during surgery was another key factor influencing ABP risk. Overfilling of the pancreatic duct with contrast agents can lead to reflux into the interstitial space and venous circulation, causing pancreatic duct visualization. This phenomenon is often associated with acinar clouding in the pancreas, which can induce chemical damage and increase ABP risk.23 To minimize this risk, LC procedures should avoid unnecessary pancreatic duct imaging, limit multiple intubations, and employ soft guidewires to reduce pancreatic juice reflux. The timing of cholecystectomy is also related to the occurrence of post-operative ABP. Studies show that if gallstones are left untreated, the recurrence rate of ABP is 32–61%.24 Early LC in patients has a lower incidence and recurrence rate. Regardless of laboratory test results and pain status, laparoscopic cholecystectomy can be safely performed within the first 48 hours for patients with gallstone-induced pancreatitis.25 It was suggested that performing laparoscopic cholecystectomy within the first 48 hours on approximately half of the patients with acute pancreatitis due to biliary causes, and the results showed significant reductions in both the occurrence of ABP and hospital stay.26

    This study also confirms that multiple biochemical markers are closely related to the pathological process of ABP. In ABP patients, TG levels are significantly elevated. The free fatty acids released by lipoprotein hydrolysis by lipase form micelle structures that directly damage pancreatic cells, leading to local ischemia and acidosis, which in turn activate proenzymes, triggering pancreatic autodigestion. The damage to acinar cells also triggers an inflammatory cascade, and unsaturated fatty acids further promote the release of inflammatory mediators.27 The study also found that D-dimer levels are significantly elevated in ABP patients, reflecting hypercoagulability and a tendency toward thrombosis. D-dimer promotes inflammatory cell infiltration and cytokine release, forming a coagulation-inflammation vicious cycle, which exacerbates pancreatic microcirculation disorder.28 Additionally, CRP, WBC, neutrophils, and RDW are all associated with ABP. CRP, as an acute-phase protein, rises rapidly within 2–12 hours after inflammation onset, playing a dual role in regulating the inflammatory response and protecting the body. WBC elevation is primarily driven by neutrophils, and their overactivation may worsen tissue damage. RDW elevation is associated with the suppression of erythrocyte maturation by pro-inflammatory factors and erythrocyte membrane damage caused by reactive oxygen species.29–31 These markers provide important basis for the diagnosis and assessment of ABP.

    Our study has several limitations that should be acknowledged. First, it is a single-center, retrospective study, which may introduce information bias and limit the ability to infer causal relationships. Second, the sample size of the validation cohort is relatively small; future studies with larger sample sizes and prospective cohort data are needed. Third, the study population consisted exclusively of patients who underwent LC, which may limit the generalizability of the predictive model to other populations. Furthermore, future research should extend the follow-up period to evaluate the long-term predictive performance of the model.

    In conclusion, the predictive model developed in this study effectively estimates the risk of post-LC pancreatitis in patients with gallstones. Calibration curves and decision curve analyses demonstrated the model’s robust predictive performance and considerable net clinical benefit. In addition, this study highlights the multifactorial nature of acute biliary pancreatitis (ABP) following LC and emphasizes the value of a predictive model that integrates both clinical and biochemical parameters. By identifying key risk factors and providing a reliable risk assessment tool, our findings contribute to the advancement of early prevention strategies and the optimization of clinical management for gallstone-related ABP. Nonetheless, further studies with larger sample sizes and prospective designs are warranted to validate the model and enhance its generalizability.

    Data Sharing Statement

    All original data can be available from the corresponding author upon request.

    Ethical Approval and Consent to Participate

    This study adhered to the principles of the Declaration of Helsinki and was approved by the Institutional Review Board of the Ethics Committee of Henan Province Hospital of Traditional Chinese Medicine (HNSZYYWZ-20241105030). The informed consent is waived by the ethics committee because this is a retrospective design study. Patient confidentiality and data privacy were strictly safeguarded throughout the study.

    Funding

    This study was supported in Special Project for Scientific Research of Traditional Chinese Medicine in Henan Province (2019DJZX054, 2023ZY1014).

    Disclosure

    The authors have no conflicts of interest.

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    12. Streck JM, Rigotti NA, Livingstone-Banks J. Interventions for smoking cessation in hospitalised patients. Cochrane Database Syst Rev. 2024;5(5):D1837. doi:10.1002/14651858.CD001837.pub4

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    22. Celik A, Ertekin C, Ercan LD. Might be over-evaluated: predicting choledocholithiasis in patients with acute biliary pancreatitis. Ulus Travma Acil Cerrahi Derg. 2025;31(3):249–258. doi:10.14744/tjtes.2024.36114

    23. Banerjee A. Different contrast agents and development of pancreatitis after endoscopic retrograde pancreatography. Am J Gastroenterol. 1992;87(5):683–684, 684–685.

    24. Sekimoto M, Takada T, Kawarada Y. JPN Guidelines for the management of acute pancreatitis: epidemiology, etiology, natural history, and outcome predictors in acute pancreatitis. J Hepatobiliary Pancreat Surg. 2006;13(1):10–24. doi:10.1007/s00534-005-1047-3

    25. Zhong FP, Wang K, Tan XQ, Nie J, Huang W-F, Wang X-F. The optimal timing of laparoscopic cholecystectomy in patients with mild gallstone pancreatitis: a meta-analysis. Medicine. 2019;98(40):e17429. doi:10.1097/MD.0000000000017429

    26. Demir U, Yazici P, Bostanci O. Timing of cholecystectomy in biliary pancreatitis treatment. Ulus Cerrahi Derg. 2014;30(1):10–13. doi:10.5152/UCD.2014.2401

    27. Berberich AJ, Hegele RA. Rapidly lowering triglyceride levels by plasma exchange in acute pancreatitis: what’s the point? J Clin Apher. 2022;37(3):194–196. doi:10.1002/jca.21972

    28. Newton MV. D-dimer as a marker of severity and prognosis in acute pancreatitis. Int J Appl Basic Med Res. 2024;14(2):101–107. doi:10.4103/ijabmr.ijabmr_483_23

    29. Huang L, Chen C, Yang L, Wan R, Hu G. Neutrophil-to-lymphocyte ratio can specifically predict the severity of hypertriglyceridemia-induced acute pancreatitis compared with white blood cell. J Clin Lab Anal. 2019;33(4):e22839. doi:10.1002/jcla.22839

    30. Panek J, Kusnierz-Cabala B, Dolecki M, Pietron J. Serum proinflammatory cytokine levels and white blood cell differential count in patients with different degrees of severity of acute alcoholic pancreatitis. Pol Przegl Chir. 2012;84(5):230–237. doi:10.2478/v10035-012-0038-8

    31. Jagodic EA, Ejubovic M, Jahic R. The role of Red Cell Distribution Width (RDW), RDW/platelet ratio, and mean platelet volume as prognostic markers in acute pancreatitis severity and complications based on the bedside index for severity in acute pancreatitis score. Cureus. 2024;16(8):e66193. doi:10.7759/cureus.66193

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  • WhatsApp developing ‘search draft messages’ feature for iPhone users

    WhatsApp developing ‘search draft messages’ feature for iPhone users





    WhatsApp developing ‘search draft messages’ feature for iPhone users – Daily Times


































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  • Women’s and girls’ sexual empowerment differs by geographical context: a population-based validation study | BMC Women’s Health

    Women’s and girls’ sexual empowerment differs by geographical context: a population-based validation study | BMC Women’s Health

    This study is the first to examine the psychometric properties and factor structure of the sexual empowerment sub-scale of the WGE-SRH Index across ten culturally diverse settings. Overall, results suggest the scale is a reliable tool for understanding how women frame and act on sexual decisions across diverse cultures in sub-Saharan Africa. After dropping two items, psychometric properties were strong in most sites, except Rajasthan, India, where item fit remained slightly below desired thresholds.

    Findings confirm a two-factor structure of sexual empowerment (existence of choice and exercise of choice), similar to that originally identified by Moreau and colleagues [17]. Notably, however, some items performed differently across contexts. In Rajasthan, India, in particular, full models showed that the item,“If I show my husband/partner that I want to have sex, he may consider me promiscuous” loaded strongly onto the existence of choice domain, while the item, “If I do not want to have sex, I am capable of avoiding it with my husband/partner” loaded strongly onto exercise of choice. In contrast, factor loadings for these two items showed considerable variability in sub-Saharan African settings, with the promiscuity item underperforming in the majority of contexts. Similarly, the “avoid” item did not meet desired thresholds in several sites. As such, both items were dropped from final models to ensure consistency across sub-Saharan African sites, however, these items may still have relevance and be considered as critical aspects of sexual empowerment within the context of research in Asia, where commonality of extramarital relationships and implications of promiscuity may differ [32,33]. Combining the sexual existence of choice and sexual exercise of choice domains into a single measure resulted in a multidimensional index of sexual empowerment with moderate to good internal reliability (alpha range 0.59 in Kongo Central, DRC to 0.69 in Niger), along with evidence of goodness of fit across sites, withstanding Rajasthan, India.

    Understanding cross-site differences in existence vs. exercise of choice is relevant for the implementation of interventions and programs seeking to counteract harmful gender norms. Marked variations were seen across sites in women’s perceptions of their partners’ responses to refusing sex, as well as their own confidence in voicing when and when not to have sex. Niger, specifically, stood out as a site with overall low exercise of choice; however, this setting was comparable to other sites for existence of choice items. Such contrast between existence and exercise of choice may be indicative of where a population lies on the empowerment pathway [15]. Of note, Niger has the highest prevalence of child marriage globally [27]. While many contexts have overcome gender and power barriers related to existence of choice surrounding sex, many women still may not feel comfortable exercising this choice. In such contexts, programs and interventions should focus on supporting women’s ability to communicate and negotiate their sexual choices, rather than normative factors prohibiting women’s sexual needs in the first place. Community dialogues, such as those implemented for intimate partner violence, may be useful to support communication and negotiation, while concurrently working with men and the broader community [34,35,36]. As opposed to contraceptive empowerment, where women can exercise their choice to use contraception via covert contraceptive use without first having the existence of choice [30,37], sex requires an interaction between sexual partners and, therefore, both existence and exercise of choice must co-exist for women to achieve volitional sex. These results point to the importance of disentangling the domains of existence vs. exercise of choice for sexual empowerment.

    Identifying within-site variation is also necessary to determine where empowerment interventions are needed or may have fallen short. Some items were particularly polarizing within contexts—specifically, the “promiscuous” item had the majority responses concentrating in strongly agree or strongly disagree categories, with few women indicating neutral empowerment (i.e., neither agreeing nor disagreeing). These polarized responses persisted for exercise of choice items across contexts and were particularly pronounced for items focusing on women’s desire to have sex rather than not to have sex. Such results highlight the sexual double standards between men and women reported in previous studies [15,38,39,40] and speak to the undervaluing of women’s sexual pleasure as a key component of their sexual health [41].

    These cross-cultural findings further elucidate that sexual empowerment is largely constrained—when examining our overall sexual empowerment scores, less than half of the sites reported the majority of women with high or highest empowerment scores (Lagos, Nigeria: 74.5%, Kenya: 58.4%, Kinshasa, DRC: 57.7%, and Rajasthan, India: 54.7%). In sites where existence and exercise of choice were in opposition (i.e., Niger, Kano, Nigeria, and Kongo Central, DRC), overall empowerment concentrated in the neutral category. Notably, these lower empowerment sites likely represent different stages of gender norms programs (i.e., focus on existence of choice rather than exercise of choice) and should continue to be examined.

    This study has several strengths, including distinguishing between sexual existence and exercise of choice and its use of ten population-based samples to validate a sexual empowerment sub-scale and compare sexual empowerment levels across sites. Nonetheless, findings should be considered in light of some limitations. Specifically, item wording pertains to a woman’s current husband/partner, precluding understanding of how these items apply within concurrent partner relationships. Women may feel empowered sexually with some partners, but not with others. Within-site variation in sexual empowerment was not examined to afford fuller exploration of sexual empowerment across populations, however, given cultural heterogeneity in practices within many study sites, this should be examined in future studies. Reasons for sexual empowerment within and across sites, as well as an understanding of who is empowered, as additionally needed. Lastly, it is noted that only one small site within Asia was included in this study (Rajasthan, India) and is not generalizable to the whole of Asia nor the whole of India.

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  • Joyful Parisians take a historic plunge into the Seine after 100 years

    Joyful Parisians take a historic plunge into the Seine after 100 years



    CNN
     — 

    For the first time in over a century, Parisians and tourists will be able to take a refreshing dip in the River Seine. The long-polluted waterway is finally opening up as a summertime swim spot following a 1.4 billion euro ($1.5 billion) cleanup project that made it suitable for Olympic competitions last year.

    Three new swimming sites on the Paris riverbank will open on Saturday – one close to Notre Dame Cathedral, another near the Eiffel Tower and a third in eastern Paris.

    Swimming in the Seine has been illegal since 1923, with a few exceptions, due to pollution and risks posed by river navigation. Taking a dip outside bathing areas is still banned for safety reasons.

    The Seine was one of the stars of the Paris Olympics in 2024, whether as the scene of the ambitious opening ceremony or the triathlon and marathon swimming competitions. That didn’t go without challenging hurdles such as rainfall increasing levels of bacteria, which postponed some competitions.

    The city’s authorities have given the green light for the public opening, with water quality results consistently in line with European regulations.

    “It’s a symbolic moment when we get our river back,” said sports coach and influencer Lucile Woodward, who will participate in the first amateur open water competition in the Seine on Sunday.

    Woodward, who enjoyed a dip alongside Paris Mayor Anne Hidalgo just before the start of the Olympic Games, is confident things will go well.

    “We’re going to enjoy swimming in it, being there and setting an example,” she said. “Once people will see that in the end there are hundreds of people who have fun and enjoy it, everyone will want to go!”

    “For families, going to take a dip with the kids, making little splashes in Paris, it’s extraordinary,” Woodward added.

    Olympic athletes competing in the river was a spectacular reward for the cost of the cleanup effort.

    In the run-up to the Games, authorities opened new disinfection units and created a huge storage basin meant to prevent as much bacteria-laden wastewater as possible from spilling directly into the Seine when it rains.

    Houseboats that previously emptied their sewage directly into the river were required to hook up to municipal sewer systems. Some homes upstream from Paris also saw their wastewater connected to treatment plants instead of the rainwater system flowing directly into the river.

    Paris Deputy Mayor Pierre Rabadan said water is tested daily to confirm it’s safe to swim. As on French beaches, different colored flags will inform visitors whether or not they can go in.

    “Green means the water quality is good. Red means that it’s not good or that there’s too much current,” he said.

    Tests have been in line with European regulations since the beginning of June, with only two exceptions due to rain and boat-related pollution, Rabadan said.

    “I can’t make a bet on the numbers of days when we’ll have to close this summer, but water quality seems better than last year,” he added. “We’re in a natural environment… so weather condition variations necessarily have an impact.”

    Last year, several athletes became ill after competing in the triathlon and open water races during the Olympics, though in most cases it was not clear if the river was to blame for their sickness.

    World Aquatics stressed the conditions met the sport’s accepted thresholds.

    “The legacy of these efforts is already evident, with the Seine now open for public swimming – a positive example of how sports can drive long-term community benefits,” the organization said in a statement to The Associated Press.

    The opening of the three Seine swimming pools, as part of the 'Paris Plages' event, happened on Saturday.

    Skepticism remains about water quality

    Dan Angelescu, founder and CEO of Fluidion, a Paris and Los Angeles-based water monitoring tech company, has routinely and independently tested bacterial levels in the Seine for several years. Despite being in line with current regulations, the official water testing methodology has limitations and undercounts the bacteria, he said.

    “What we see is that the water quality in the Seine is highly variable,” Angelescu said. “There are only a few days in a swimming season where I would say water quality is acceptable for swimming.”

    “All we can say is that we can raise a hand and say look: the science today does not support the current assessment of water safety used in the rivers around Paris, and we think that there is major risk that is not being captured at all,” he said.

    Some Parisians also have shown skepticism toward the idea of swimming in the Seine. The feeling is often reinforced by the water’s murky color, floating litter and multiple tourist boats in some places.

    Enys Mahdjoub, a real estate agent, said he would not be afraid of swimming, but rather “a bit disgusted. It’s more the worry of getting dirty than anything else at the moment.”

    Until the end of August, swimming sites will be open for free at scheduled times to anyone with a minimum age of 10 or 14 years, depending on the location. Lifeguards will keep a watchful eye on those first dips.

    “It’s an opportunity, a dream come true,” said Clea Montanari, a project manager in Paris. “It’d be a dream if the Seine becomes drinkable, that would be the ultimate goal, right? But already swimming in it is really good.”

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  • ‘Can we safely use that?’

    ‘Can we safely use that?’

    Would you believe that the probiotics found in yogurt could help make batteries safer? A team of scientists at Binghamton University proved that it’s possible, Interesting Engineering reported.

    The researchers managed to build a battery using a paper material that dissolves in water and

    probiotic bacteria. That’s right: The same organisms that boost your gut health after drinking a smoothie were engineered to produce electricity using a special electrode.

    The result was a power source that can basically self-destruct after a set amount of time without harming its surroundings, Interesting Engineering explained.

    A big problem with batteries is that many contain toxic chemicals. After they are used, this pollution often enters soil and water through landfills and can end up posing dangers to human health.

    Yet with the researchers’ solution, clean power can flow where it needs to flow, and afterward, no one gets hurt. Their model can currently run between four and 100 minutes before it cleanly and safely destroys itself. All that remains are helpful microbes, Interesting Engineering reported.

    Watch now: Does clean energy really cause blackouts?

    This kind of battery is part of a field called transient electronics, which is all about fuel cells that are not made to last. Instead, they are designed to disintegrate, much like a device from a “Mission: Impossible” movie, Interesting Engineering noted.

    That might sound impractical, but there are actually all kinds of useful homes for these batteries that save time and money. For example, they make medical implant procedures simpler and safer, improve sustainable environmental sensors, and make disposable electronics cleaner and secure, per Interesting Engineering.

    “Whenever I made presentations at conferences, people would ask: So, you are using bacteria? Can we safely use that?” explained Maedeh Mohammadifar, who developed the original dissolvable battery during her time as a graduate student. She affirmed that the selected probiotics were common and safe to use, according to the outlet.

    The full research findings are published in the journal Small.

    Join our free newsletter for weekly updates on the latest innovations improving our lives and shaping our future, and don’t miss this cool list of easy ways to help yourself while helping the planet.

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  • Astronaut Photographs Lightning Tower That Looks Like Something Evil From “Lord of the Rings”

    Astronaut Photographs Lightning Tower That Looks Like Something Evil From “Lord of the Rings”

    Red Sprite

    NASA astronaut Nichole Ayers, currently stationed on board the International Space Station, shared an incredible image of a sprite — a rare weather phenomenon that’s triggered high above the clouds by “intense electrical activity in the thunderstorms below.”

    The image shows the rare electrical discharge in the shape of a starkly red, upended umbrella, hovering high over a brewing storm, like some sort of occult tower from “Lord of the Rings.”

    “Just. Wow,” Ayers tweeted. “As we went over Mexico and the US this morning, I caught this sprite.”

    Being hundreds of miles above the surface of the Earth gave Ayers the perfect vantage point to watch the stunning event unfold.

    “We have a great view above the clouds, so scientists can use these types of pictures to better understand the formation, characteristics, and relationship of [Transient Luminous Events] to thunderstorms.”

    Seven Up

    According to NASA, sprites can appear at altitudes of around 50 miles, which is far higher than where thunderstorms form. They often appear mere moments after lightning strikes, forming spiny tendrils of red plumes.

    The otherworldly phenomenon, which was first officially observed in 1989 photographs, is still poorly understood. Scientists have yet to uncover how and why they form.

    In 2022, NASA launched a “citizen science project,” dubbed “Spritacular,” to crowdsource images of the TLEs. According to the project’s official website, over 800 volunteers have joined the effort, and 360 observations have been collected across 21 countries.

    Other TLEs include elves, an acronym for “emission of light and very low frequency perturbations due to electromagnetic pulse sources,” and jets, a type of cloud-to-air discharge that can appear as blue tendrils.

    “While sprites [and other TLEs] may appear delicate and silent in the upper atmosphere, they are often linked to powerful, sometimes devastating weather systems,” University of Science and Technology of China PhD student and TLE expert Hailiang Huang told National Geographic last week.

    “Understanding them not only satisfies our curiosity about the upper atmosphere, but also helps us learn more about the storms we face here on Earth,” he added.

    Best of all, studying TLEs could even help us learn about distant planets: NASA’s Juno mission found evidence of sprites and elves in the atmosphere of Jupiter as well.

    More on sprites: NASA Crowdsourcing Investigation of Otherworldly “Sprites” in Sky


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  • Everything You Can Do in the Photoshop Mobile App

    Everything You Can Do in the Photoshop Mobile App

    You know your software is a success when its name becomes a verb: You’ll now commonly hear about images being photoshopped, even if the editing wasn’t done with the Adobe image editor. Adobe might not like it, but the usage shows how dominant its flagship product has become.

    On mobile though, Photoshop hasn’t achieved the same kind of ubiquity or brand recognition. We’ve had official Photoshop apps of various types down the years, but none of them have really translated the power and feature set of the desktop application over to smaller devices in a way that fully works.

    Now, Adobe is trying again: The all-new Photoshop app (available now for iOS, and just released in beta for Android), is Photoshop “reimagined” for a smartphone. The app attempts to bring over as many of the tools and features of the full software as it can, while optimizing them for use on a mobile touchscreen.

    While it’s impossible to port everything over—in the same way macOS wouldn’t work on an iPhone—there’s a lot to explore in the new Photoshop app. You can download it for free on iOS, though some features require a premium subscription (either $7 a month for the new Mobile and Web plan, or an existing Photoshop plan). Android users can download the beta version and use it entirely for free for a limited time. Regular pricing will kick in when the app becomes generally available worldwide.

    Quick Actions

    By default, when you open up a new image in the iOS version, you’ll be invited to apply a “quick action” to it. (Android users, this is coming soon.) If you’d rather just go straight to the full editing interface every time, check the Don’t show this again box, and tap Go to editor. However, if you are wanting to apply a basic effect in as little time as possible, these quick actions can be helpful.

    You’ll see they all involve backgrounds. Tap Hide background, and Photoshop tries to identify the main subject of the image, and cut out the rest—you can then drop in any kind of replacement background you like. Alternatively, there’s Solid color background, which drops in a color you can edit, or Black & white background, which keeps the subject in color but turns everything else grayscale.

    Whichever one you pick, Photoshop will take care of creating a new layer for you, so you can work on the foreground and background independently. You’ll see the layers are available via the thumbnail down in the lower right corner of the image. With the solid color background, for example, tap the layer thumbnail, then the left arrow, then Edit color to switch to a different shade.

    Layers and Masks

    Choosing an adjustment layer.

    Courtesy of Michael Calore / WIRED

    Layers and masks are essentially what separates basic image editors from advanced ones, letting you stack different elements in an image on top of each other (layers) and make edits to them (masks). If you’ve used a quick action you’ll already have a layer created for you, but you can create new ones by tapping the + (plus) button just above the bottom toolbar on the right.

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