Category: 3. Business

Consumers and the UK financial system are being exposed to “serious harm” by the failure of government and the Bank of England to get a grip on the risks posed by artificial intelligence, an influential parliamentary committee has warned.

In a new report, MPs on the Treasury committee criticise ministers and City regulators, including the Financial Conduct Authority (FCA), for taking a “wait-and-see” approach to AI use across the financial sector.

That is despite looming concerns over how the burgeoning technology could disadvantage already vulnerable consumers, or even trigger a financial crisis, if AI-led firms end up making similar financial decisions in response to economic shocks.

More than 75% of City firms now use AI, with insurers and international banks among the biggest adopters. It is being used to automate administrative tasks or even help with core operations, including processing insurance claims and assessing customers’ credit-worthiness.

But the UK has failed to develop any specific laws or regulations to govern their use of AI, with the FCA and Bank of England claiming general rules are sufficient to ensure positive outcomes for consumers. That means businesses have to determine how existing guidelines apply to AI, leaving MPs worried this could put consumers and financial stability at risk.

“It is the responsibility of the Bank of England, the FCA and the government to ensure the safety mechanisms within the system keeps pace,” said Meg Hillier, chair of the Treasury committee. “Based on the evidence I’ve seen, I do not feel confident that our financial system is prepared if there was a major AI-related incident and that is worrying.”

The report flagged a lack of transparency around how AI could influence financial decisions, potentially affecting vulnerable consumers’ access to loans or insurance. It said it was also unclear whether data providers, tech developers or financial firms would be held responsible when things went wrong.

MPs said AI also increased the likelihood of fraud, and the dissemination of unregulated and misleading financial advice.

In terms of financial stability, MPs found that rising AI use increased firms’ cybersecurity risks, and left them overly reliant on a small number of US tech companies, such as Google, for essential services. Its uptake could also amplify “herd behaviour”, with businesses making similar financial decisions during economic shocks and “risking a financial crisis”.

The Treasury committee is now urging regulators to take action, including the launch of new stress tests that would assess the City’s readiness for AI-driven market shocks. MPs also want the FCA to publish “practical guidance” by the end of the year, clarifying how consumer protection rules apply to AI use, and who would be held accountable if consumers suffer any harm.

“By taking a wait-and-see approach to AI in financial services, the three authorities are exposing consumers and the financial system to potentially serious harm”, the report said.

The FCA said it had already “undertaken extensive work to ensure firms are able to use AI in a safe and responsible way”, but would review the report’s findings “carefully”.

A spokesperson for the Treasury said: “We’ve been clear that we will strike the right balance between managing the risks posed by AI and unlocking its huge potential.”

They added that this involved working with regulators to “strengthen our approach as the technology evolves”, and appointing new “AI champions” covering financial services “to ensure we seize the opportunities it presents in a safe and responsible way”.

A spokesperson for the Bank of England said it had “already taken active steps to assess AI-related risks and reinforce the resilience of the financial system, including publishing a detailed risk assessment and highlighting the potential implications of a sharp fall in AI-affected asset prices. We will consider the committee’s recommendations carefully and will respond in full in due course.”

Track your investments for FREE with Simply Wall St, the portfolio command center trusted by over 7 million individual investors worldwide.

BlackBerry (TSX:BB) has caught investor attention after a mixed run in its share price, with the stock showing a gain over the past month alongside a decline in returns over the past three months and the past year.

See our latest analysis for BlackBerry.

At a current share price of CA$5.40, BlackBerry’s recent 30 day share price return of 4.25% contrasts with a 90 day share price decline of 17.43% and a 1 year total shareholder return decline of 6.90%, suggesting momentum has been fading after a short term bounce.

If BlackBerry’s mixed performance has you reassessing your watchlist, this could be a good moment to check out high growth tech and AI stocks as another way to spot opportunities in software and security focused names.

With BlackBerry posting annual revenue of $534.8 million, net income of $21.1 million and an intrinsic value estimate suggesting roughly a 14% discount, you have to ask: is this a genuine entry point, or is the market already pricing in future growth?

BlackBerry trades on a P/E of 108.5x, which, at a CA$5.40 share price, points to a rich earnings multiple compared with both peers and its own fair value markers.

The P/E ratio compares the current share price with earnings per share. For a software and security focused company like BlackBerry, it often reflects how much future earnings growth investors are willing to pay for today.

Here, the market price implies investors are paying more for each dollar of earnings than for the average Canadian software stock, with BlackBerry on 108.5x versus an industry average of 45.5x and a peer group average of 52.1x. Our estimated fair P/E of 35.4x is also far lower than the current multiple. This suggests a level that prices in a more moderate view of future earnings than the market currently does.

Explore the SWS fair ratio for BlackBerry

Result: Price-to-Earnings of 108.5x (OVERVALUED)

However, BlackBerry’s rich 108.5x P/E and 5 year total shareholder return decline of 76.44% highlight sentiment risks if earnings or execution disappoint from this point onward.

Find out about the key risks to this BlackBerry narrative.

While the 108.5x P/E suggests BlackBerry is expensive, our DCF model points the other way. With an estimated fair value of CA$6.27 versus today’s CA$5.40, the shares sit around 14% below that mark. Is the high multiple a warning sign, or is the DCF hinting at mispriced potential?

Look into how the SWS DCF model arrives at its fair value.

Simply Wall St performs a discounted cash flow (DCF) on every stock in the world every day (check out BlackBerry for example). We show the entire calculation in full. You can track the result in your watchlist or portfolio and be alerted when this changes, or use our stock screener to discover 866 undervalued stocks based on their cash flows. If you save a screener we even alert you when new companies match – so you never miss a potential opportunity.

If you see the numbers differently, or simply prefer to piece together your own view from the data, you can build a custom thesis in just a few minutes with Do it your way.

A great starting point for your BlackBerry research is our analysis highlighting 3 key rewards and 1 important warning sign that could impact your investment decision.

If BlackBerry has sparked fresh questions about where to focus next, do not stop here, there are plenty of other angles worth your attention right now.

This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.

Companies discussed in this article include BB.TO.

Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team@simplywallst.com

Key Facts

Chief Critic

“I would pay no attention whatsoever to Elon Musk, he’s an idiot,” said Ryanair CEO Michael O’Leary in a podcast late last week, sparking Musk’s rage. “Very wealthy, but he’s still an idiot.”

Big Number

$200 million-$250 million per year. That’s the annual cost of installing an aerial antenna needed to access Starlink satellites on top of an aircraft, according to O’Leary, who described Musk’s services as unaffordable.

Key Background

In a podcast clip posted Thursday, O’Leary rejected the idea of installing SpaceX’s Starlink satellite internet service on Ryanair aircraft, saying Elon Musk knows “zero” about flights and drag. The next day, Musk publicly responded to the clip by calling O’Leary “an utter idiot,” adding, “Fire him.” That prompted a user to suggest he buy Ryanair and fire O’Leary, sparking Musk’s interest, who responded with “Good idea.” Shortly after X suffered a sitewide outage on Friday, Ryanair’s account, which is known for its witty posts, poked fun at Musk, asking, “Perhaps you need Wi-Fi.” That’s when Musk hit back by suggesting that he might try to buy Ryanair and put a person named Ryan in charge, garnering 9.5 million impressions as of Monday afternoon.

The world’s oldest monastic brewery, Germany’s Weltenburger, is being sold to the Munich brewers Schneider Weisse as part of consolidation in the sector in response to plunging sales.

Beer has been brewed at Weltenburg Abbey, a stunning, still active monastery on the banks of the Danube in Bavaria, for nearly 1,000 years.

Although the facility is still owned by the Catholic church, the Benedictine monks handed over production of the brand’s award-winning lager and signature dark brews half a century ago to hired staff from the Bischofshof brewery, which will also be sold to Schneider.

The diocese of Regensburg and Schneider Weisse agreed on the sale after several years in which Weltenburger’s business was in the red, meaning the church had to inject its own funds to prop it up, local media reported.

Till Hedrich, the managing director of both Weltenburger and Bischofhof, said the planned solution could head off the threat of complete closure or break-up of the breweries by an investor with “no connection to the region”, while preserving an “important piece of Bavarian brewing tradition” in the long run.

The financial details of the sale of Weltenburger to Schneider, a comparatively young outfit launched in 1872, have not been released. But the purchase is scheduled to be completed by January 2027 and keep the 21 Weltenburger employees onboard.

“In addition to the aspect of tradition, it is very important to us that we can keep at least some of the jobs directly in the region,” the Regensburg bishop, Rudolf Voderholzer, said.

Bischofshof, which was founded in 1649 and employs 56 people, is to halt production at the end of the year, when the beer’s brand will move to Schneider.

Weltenburger will continue to be made at the historic abbey, while the Regensburg diocese said it was seeking placement for the Bischofshof workers made redundant.

Weltenburger brewery said on its website it had withstood “several fires, floods, destruction and secularisation as well as a world war” in which an order to blow up the entire complex was narrowly thwarted. It now welcomes half a million visitors a year.

“Those who cannot enjoy themselves will eventually become unbearable to others,” the monastery’s abbot, Thomas M Freihart, said, quoting Friedrich Schiller, as Weltenburger beer celebrated its 975th anniversary last May. He added: “The enjoyment of barley juice should be seen as a gift from God.”

German beer sales, however, are on a downward slide, as alcohol consumption falls in many western countries, including Britain. Turnover has shrunk by a quarter in the last 15 years, according to Germany’s main industry body. In 2025, consumption fell by 5m hectolitres, the biggest decline in 75 years.

The German beer market has maintained a standout tradition of fealty to regional brands, with a few dozen nationally or globally known names jostling for drinkers against the output of about 1,500 small and medium-sized breweries.

In most countries where major brands dominate, they have swallowed smaller historic breweries, with only bespoke craft breweries putting up a modest fight.

As a result Germany, perhaps surprisingly given its long and proud tradition, does not have a single brew among the world’s top 10 selling beers.

It does, however, still boast the largest number of monastic breweries, nine managed by monks or their employees and a 10th, the Franciscan convent Mallersdorf Abbey, run by nuns who only sell the small surplus of what they do not drink themselves.

Beer brewing and consumption are believed to date back to at least the Neolithic period but it was monasteries in the middle ages that turned them into a business.

Of late, beer has suffered from an image problem in Germany as consumers turn their backs on alcohol. Often seen as a fusty drink of older generations, classic beers are bound by Germany’s “purity law”, known as the Reinheitsgebot, a medieval food safety rule which deemed that beer could contain nothing other than water, barley, hops and, later, also yeast.

It has made innovation a challenge, even as non-alcoholic brews gain in popularity.

This article first appeared on GuruFocus.

Micron Technology (MU, Financials) is deepening its roots in Taiwan with a $1.8 billion agreement to buy Powerchip Semiconductor Manufacturing Corp.’s P5 fabrication plant, a move aimed at meeting the growing appetite for memory chips that power artificial intelligence systems.

The Idaho-based chipmaker said the deal will add about 300,000 square feet of cleanroom space at the Tongluo, Miaoli County site. Micron expects the facility to begin contributing to dynamic random access memory wafer production in the second half of 2027. The added capacity comes as global demand for advanced memory continues to outpace supply, with AI servers, smartphones, and cloud computing driving the next wave of chip consumption.

Powerchip’s shares climbed nearly 10% after the announcement, reflecting investor optimism about the long-term partnership between the two companies. Powerchip said Micron will not only purchase the facility but also collaborate on specialty DRAM process technologies and advanced packaging.

Micron is one of the world’s top three producers of high bandwidth memory, alongside Samsung and SK Hynix, and has operated in Taiwan for more than three decades. The island remains a cornerstone of Micron’s manufacturing network and a hub for DRAM and high performance chip production.

Micron’s CEO, Sanjay Mehrotra, has said tight memory markets could persist beyond 2026. The company’s stock surged 240% last year, far outpacing the broader semiconductor index.

Introduction

Placenta accreta spectrum (PAS) is a serious obstetric complication usually associated with abnormal attachment or invasion of the placenta into the myometrium,¹ which may lead to life-threatening postpartum hemorrhage and hysterectomy.² Indeed, placental implantation spectrum disorders include several types: placental adhesion (anchoring villi attached to the superficial myometrium without insertion into the meconium), placental implantation (infiltration of placental villi into the myometrium), and penetrative placental implantation (anchoring villi tissue penetrating the entire uterine wall and even reaching surrounding organs).³ In recent years, the incidence of PAS has risen significantly with the rising rate of cesarean section and the increasing age of pregnant women.⁴ In order to accurately predict PAS and its associated risks in the prenatal period, researchers have developed various magnetic resonance imaging (MRI)-based prediction models. For example, Maurea et al proposed a model that utilizes ultrasound and MRI features (eg, loss of posterior interstitial space, intra-placental dark bands, and focal interruption of myometrial borders) to predict the risk of PAS in patients with placenta previa.⁵ Andrea et al developed an MRI-based scoring system that, by evaluating indicators such as T2 dark bands, uterine myometrial thinning, and abnormal vascular distribution, has further improving the diagnostic accuracy of PAS.⁶

However, most of these models do not adequately consider the morphological characteristics of the cervix and placenta. In recent years, it has been shown that placental volume and cervical length are closely associated with the occurrence of PAS and the risk of postpartum hemorrhage. In a study by Yue et al it was found that patients with smaller cervical areas and shorter cervical lengths had significantly more intraoperative hemorrhage and a higher incidence of adverse pregnancy outcomes in the presence of a complete placenta previa.⁷ And a study by Yue et al further confirmed that increased placental volume and T2 dark band volume were positively associated with the risk of major bleeding in patients with PAS.⁸ These findings suggest that morphological characteristics of the placenta and cervix are valuable in risk assessment of PAS.

Based on these studies, this study innovatively combined cervical volume, placental volume, and cervical length to construct a novel PAS risk prediction model. By quantifying these morphological indicators, we aimed to provide clinicians with a more accurate prenatal prediction tool to help them better assess the likelihood of PAS in patients with complete placenta previa who have a history of cesarean delivery. The establishment of this model not only fills the gap of previous studies in cervical and placental morphology, but also provides new ideas for early diagnosis and risk stratification of PAS, which is of great clinical significance.

Materials and Methods

This study was reviewed by the Ethics Committee of Suzhou Hospital of Nanjing Medical University (Approval K-2022-015-K01). Informed consent was waived because this anonymously selected study was retrospective and no new interventions were performed on patients. We reviewed the clinical data of pregnant women with complete placenta previa from January 2018 to August 2024 who had a history of cesarean delivery. Inclusion criteria were: pregnant women with MRI-confirmed diagnosis of complete placenta previa. Exclusion criteria were: (1) twin or multiple pregnancies, (2) no previous history of cesarean section, (3) no pelvic MRI, (4) incomplete clinical or surgical data, and (5) poor image quality affecting observation. The flow chart of the study design is shown in Figure 1. The reason for this design is that MRI is a key tool in the diagnosis of complete placenta previa and placenta implantation spectrum disorders (PAS), providing clearer images than ultrasound and ensuring diagnostic accuracy. By requiring all study subjects to undergo MRI, bias introduced by inconsistent diagnostic tools can be avoided, ensuring homogeneity and reliability of the study data. Ultimately, a total of 157 patients were included in the study, and the diagnosis of PAS was based on the 2019 FIGO criteria.

Figure 1 Flow chart of PAS patients with complete placenta previa included in the study.

MRI scans were performed at 3t (Siemens Medical Solutions, Erlangen, Germany) without gadolinium and keeping the bladder partially filled for optimal evaluation of the bladder-plasma membrane interface. Most patients were examined in the supine position, and a few patients who could not tolerate the supine position were examined in the left lateral position. MRI image acquisition employs a T2-weighted half-Fourier single-pass turbo spin-echo sequence to obtain axial, sagittal, and coronal images covering the entire uterus.

Cervical volume, placental volume, and cervical length were measured by three radiologists with over 20 years of experience in obstetric and gynecologic MRI. Radiologists were unaware of all clinical information and other radiologists’ impressions. First, MRI images from patients with complete placenta previa were imported into 3D Slicer software (version 5.2.1, www.slicer.org) to create placental and cervical contours and measure placental and cervical volumes with coronal, sagittal, and axial views of the placenta as shown (Figure 2A–C). Subsequently, MRI images from patients with complete placenta previa were imported into ImageJ software version 1.50 (National Institutes of Health, Bethesda, USA) to measure cervical length. The measurement method involved lines a and b passing through the internal and external cervical canals, respectively, and perpendicular to the cervical canal. The shortest distance between these two lines represented the cervical length (Figure 2D). After segmentation in 3D Slicer software, its 3D reconstruction function generated three-dimensional models of the placenta and cervix. The main steps were as follows: (1) Import the patient’s original MRI images in DICOM format; (2) Run the Editor module in the 2D window; (3) Perform segmentation by manually tracing the external contours of the placenta and cervix on each slice; (4) Utilize the program’s 3D segmentation function to calculate the volumes of all placental and cervical voxels (Figure 2E and F).

Figure 2 Magnetic resonance imaging (MRI) and three-dimensional (3D) reconstruction of the placenta and cervix in a patient with placenta accreta spectrum (PAS). (A) Coronal T2-weighted MRI view of the placenta.(B) Sagittal T2-weighted MRI view of the placenta.(C) Axial T2-weighted MRI view of the placenta.(D) Measurement of cervical length (2.62 cm) on a sagittal T2-weighted MRI. Line a passes through the internal cervical os, line b passes through the external cervical os, and both are drawn perpendicular to the cervical canal. The double-headed arrow indicates the cervical length, defined as the shortest distance between the two lines.(E) 3D reconstruction model of the cervix, generated using 3D Slicer software.(F) 3D reconstruction model of the placenta, generated using 3D Slicer software.

Statistical Analysis

The normality of continuous variables was assessed using the Kolmogorov–Smirnov test. Normally distributed variables were expressed as mean ± standard deviation, and intergroup comparisons were performed using the independent samples t-test. Non-normally distributed variables were expressed as median (interquartile range), and intergroup comparisons were performed using the Mann–Whitney U-test. Categorical variables were expressed as case numbers (percentages). Inter-observer agreement in MRI feature assessment was measured using the Kappa coefficient. Pearson correlation analysis explored associations between cervical volume, placental volume, cervical length, and PAS. Receiver operating characteristic (ROC) curve analysis determined optimal cutoff values for MRI features predicting PAS, with corresponding sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) calculated. Sample size estimation was performed using PASS software (version 11.0.7). The current sample size of 157 cases achieves over 90% test power at an α=0.05 level. All statistical analyses were conducted using IBM SPSS Statistics software (version 23.0). P < 0.05 was considered statistically significant.

Results

In the current study, we performed transabdominal ultrasound and MRI on 157 women who had undergone at least one cesarean section and were confirmed to have complete placenta previa, all of whom had delivered at our healthcare facility. Of these, 72 had placenta accreta (PAS), while the remaining 85 did not. Table 1 details the clinical characteristics of these patients. The mean differences in continuous variables such as age and weight between the two groups were assessed using t-tests. Z-scores were employed to compare the distribution differences of continuous variables between the two groups. For categorical variables (eg, parity, surgical history), the differences in proportions between the two groups were evaluated using chi-square (χ²) tests. By comparing the general clinical data, we found that maternal age, body mass index (BMI), gestational age, number of deliveries, history of dilatation and curettage, history of cesarean section, gestational age as revealed by MRI, and perioperative hemorrhage did not differ significantly between the two groups (P > 0.05). This finding may be related to multiple factors. All patients in the study had a history of cesarean delivery, which means that the two groups were already similar in the baseline characteristic of history of cesarean delivery, and thus the number of cesarean deliveries may no longer be a key factor in distinguishing PAS from non-PAS in this particular population. Second, although the number of cesarean deliveries is an important risk factor for PAS, other factors such as placental volume, cervical volume, and cervical length may have played a more significant role in the development of PAS in this study. In addition, the limitations of the sample size may have led to a statistical failure to detect differences in the number of cesarean deliveries. Therefore, although a history of cesarean delivery is a known risk factor for PAS, other factors may have been more critical in the specific population of this study, resulting in a history of cesarean delivery that was not significantly different between the two groups. In addition, we performed a three-dimensional reconstruction using 3D Slicer software and calculated placental volume, cervical volume, and cervical length. Interobserver variability in MRI images was nearly consistent, with Kappa values for cervical length, cervical volume, and placental volume all exceeding 0.900 (see Table 2). Of particular importance, we found that the placental volume of PAS pregnant women was significantly greater than that of non-PAS pregnant women, while their cervical volume and cervical length were significantly smaller than those of non-PAS pregnant women, and these differences were statistically significant (P < 0.001), as detailed in Table 3.

Table 1 Clinical Characteristics of Study Participants

Table 2 Interobserver Reliability of Magnetic Resonance Imaging (MRI) in the Measurement of MRI Features

Table 3 MRI Signs Related to PAS in Caesarean Section

To explore in more depth the risk factors for the development of placental implantation disease (PAS) in patients with complete placenta previa with a history of cesarean delivery, we plotted two subject operating characteristic (ROC) curves (Figure 3). In this case, the dashed line demonstrates the role of three indicators, placental volume, cervical volume, and cervical length, in predicting the occurrence of PAS. From the ROC curve analysis, we identified optimal threshold values for placental volume (880.0 cm³), cervical volume (20.0 cm³), and cervical length (3.0 cm) (Figure 4), which are important for distinguishing between pregnant women who are likely to develop PAS and those who are unlikely to do so. Subsequently, we created a novel predictive model based on these thresholds. The model was designed to explore the complex relationship between cervical volume, placental volume, and cervical length and the likelihood of PAS in pregnancies with complete placenta previa with a history of cesarean delivery. To assess this relationship more visually, we further developed a scoring system (shown in Table 4). The design of the scoring system was based on the Odds Ratio (OR) value of each indicator, ie, their independent predictive value for the occurrence of PAS. The OR for cervical volume was 4.132, for cervical length was 2.875, and for placental volume was 2.076. These ORs reflect the strength of the association between each indicator and the occurrence of PAS, with a higher OR indicating a stronger prediction of PAS by that indicator. Thus, cervical volume was assigned a score of 2, while cervical length and placental volume had relatively low OR values and were assigned a score of 1 each. Based on the scores, patients were categorized into low-risk (0–1), intermediate-risk (2) and high-risk (3–4) groups, with 76 cases in the low-risk group and 13 cases (17.1%) with combined PAS disease, 33 cases in the intermediate-risk group with combined PAS (21 cases (63.6%)) and 47 cases in the high-risk group with combined PAS (38 cases (80.9%)), which shows that with the increase in the scores, the incidence of the probability of PAS disease increases (Figure 5). In order to verify the accuracy of the scoring system, we again plotted a ROC curve (solid line). This curve demonstrates the predictive effect of the score after scoring assignment on the occurrence of PAS in those with complete placenta previa with a history of cesarean delivery. The results showed that the AUC value of the dashed line (raw index) was 0.891, while the AUC value of the solid line (scoring system) was 0.902. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for predicting PAS based on individual signs are shown in Table 5. When combined with cervical length, cervical volume, and placental volume, the sensitivity, specificity, PPV, and NPV for predicting PAS were 87.305%, 83.946%, 82.163%, and 88.645%, respectively. When applying the scoring system to predict PAS, the sensitivity, specificity, PPV, and NPV were 88.723%, 84.209%, 82.663%, and 89.817%, respectively. The high agreement between the two curves indicates that the scoring system we developed has a high accuracy in predicting the occurrence of PAS. This provides a powerful tool for assessing the risk of PAS in patients with complete placenta previa who have a history of cesarean delivery.

Table 4 PAS Index in Complete Placenta Previa with Prior Cesarean (PIPs)

Table 5 Receiver Operating Characteristic Analysis for Prediction of PAS Based on Cervical Volume, Cervical Length, and Placental Volume

Figure 3 Receiver operator characteristic curves for the regression model with cervical length, cervical volume, and placental volume, and for prediction score. Dashed line AUC= 0.891. solid line AUC= 0.902.

Figure 4 Multivariate logistic regression analysis of risk factors for patients with PAS.

Figure 5 Simple scoring model evaluated for correspondence with PAS.

Discussion

Previous studies have shown that the risk of placenta previa (PP) is usually associated with previous cesarean section, increases with the number of previous CS, and is an independent risk factor for PAS.⁹ In addition, PP combined with scarred uterus significantly increases the risk of developing PAS.^10,11 Therefore it is crucial to accurately predict the likelihood of PAS in women with placenta previa with a history of cesarean section in the antenatal period, which enables adequate preoperative preparation, for example, by planning the delivery in a referral labor ward, where more necessary means (blood transfusion, interventional radiology, resuscitation and surgical skills, etc.) are available.¹² When women with PAS deliver in a tertiary referral center with an experienced multidisciplinary team, maternal mortality and complication rates associated with PAS are significantly reduced.^13–16

In recent years, several researchers have also created different ultrasound scoring systems to help clinicians effectively predict PAS and adverse clinical outcomes before delivery. Zou¹⁷ et al scored the number of previous cesarean deliveries, placental position, placental/uterine augmentation, placental heterogeneity, placental T2 dark bands, intra-placental vascular anomalies, placental bed vascular anomalies, loss of the T2 low-signal interface, interruption of the bladder wall, penetrating PI and muscle thinning and interruption to investigate whether magnetic resonance imaging can effectively predict the diagnosis of malignant placenta previa with or without PAS and adverse clinical outcomes. In addition, Tovbin.¹⁸ created a new ultrasound scoring system that scored the number and size of placental sockets; occlusion of the boundary between the uterus and the placenta; placental position; color Doppler signals within the placental sockets; vascular richness of the placenta-bladder and/or utero-placental interface area; and number of previous cesarean deliveries. It was found that all ultrasound criteria of the scoring system were significantly associated with pathologically adherent placenta (MAP) (P<0.001). This provides additional and stronger imaging evidence for the diagnosis of MAP. Correct prenatal diagnosis buys more time for the multidisciplinary team to plan the delivery, which will help to reduce surgical complications, maternal blood loss, and length of stay in the intensive care unit.^14,19,20

In contrast to previous studies, the scoring system created in this study incorporated cervical morphology, and we chose placental volume, cervical volume, and length as key predictors of PAS based primarily on their pathophysiologic relevance. Increased placental volume usually reflects hyperplasia of placental tissue, especially in pregnant women with a history of cesarean section, where damage to the endometrium and myometrium may lead to abnormal invasion of placental villi into the myometrium, which may in turn increase the risk of PAS. Yue et al showed that the of PAS in patients with a placental volume greater than 887 cm³ was 85.531%, and the specificity was 83.907%, which indicating that placental volume is an important predictor of PAS.²¹ Shorter cervical length and volume were negatively associated with the severity of PAS and the risk of hemorrhage. Shorter cervical length usually means that the placenta may have invaded the cervical region, leading to disruption of cervical structures and abnormal vascular distribution. Yue et al found that patients with cervical length less than 30 mm had a significantly increased risk of hemorrhage, and cervical length was negatively correlated with hemorrhage volume.⁷ Based on these studies, this study innovatively combined cervical volume, placental volume and cervical length to construct a new PAS risk prediction model.

Notably, the results of this study indicate that the proportion of anterior placenta was significantly higher in the PAS group than in the non-PAS group (62.5% vs 41.2%, P = 0.008). This difference may be related to the fact that uterine scars after cesarean section are often located on the anterior wall, making the placenta more likely to attach to this area. Despite differences in placental location distribution between groups, this model’s advantage lies in its independence from placental location as a single variable. Instead, it achieves precise disease risk assessment by directly capturing PAS-induced morphological end changes in the cervix and placenta—such as reduced cervical volume and increased placental volume. Consequently, this model demonstrates greater universality. Regardless of whether the placenta is located in the anterior or posterior wall, characteristic morphological alterations can be effectively identified, achieving high predictive performance (AUC = 0.902).

The International Society for Abnormal Invasive Placenta (IS-AIP) has proposed several criteria for MRI signs of PAS, including Focal exophytic mass, Myometrial thinning, Bladder wall interruption, Abnormal vascularization of the placental bed, etc.¹² These MRI signs suggested by IS-AIP are high risk signals for PAS. In contrast, the present study identified PAS by measuring placental volume, cervical volume, and cervical length, which provides new MRI signs for prenatal prediction of PAS. It is noteworthy that the scoring system achieves quantitative evaluation by assigning corresponding points to each parameter: cervical length (CL) < 3.0 cm receives 1 point, cervical volume (CV) < 20.0 cm³ receives 2 points, and placental volume ≥ 880.0 cm³ receives 1 point. Thus, pregnant women meeting all these criteria achieve the maximum score of 4 points. Based on this scoring, patients with 3–4 points belong to the high-risk group for PAS disease. For example, PA patients with a history of CS who have CL < 3.0, CV < 20.0, and PV ≥ 880.0 strongly suggest concomitant PAS disease. This approach reduces diagnostic subjectivity to some extent. Thus, this scoring system offers clinicians a novel approach for prenatal assessment of PAS occurrence probability.

Furthermore, numerous previous studies have demonstrated associations between molecular biomarkers such as Cripto-1, AFP, and PAPP-A with PAS and placenta previa. Serum Cripto-1 levels in patients with PAS were significantly higher than in those with PP but without pregnancy complications. Elevated AFP levels during mid-pregnancy independently predicted PAS requiring hysterectomy, while elevated PAPP-A correlated with PAS and postpartum hemorrhage volume. In the future, integrating biomarkers like Cripto-1, AFP, and PAPP-A with imaging morphological parameters into predictive models may further enhance the comprehensiveness and accuracy of PAS prediction.

This study has several limitations. First, its retrospective design carries a risk of selection bias, and the limited sample size prevented complete matching between the PAS and non-PAS groups. Second, discrepancies between specimen collection times and disease diagnosis times in some laboratories may have affected the accuracy of certain indicators. Third, while inter-observer agreement was assessed and demonstrated good reproducibility (Kappa > 0.9), intra-observer variability was not analyzed. Although all measurements were performed by uniformly trained radiologists, future studies may incorporate automated segmentation techniques to further enhance measurement efficiency and objectivity. Finally, placental position, as a potential confounding factor, requires further clarification regarding its independent contribution to PAS occurrence alongside cervical-placental morphological parameters. Subsequent prospective studies with larger samples should employ multivariate or stratified analyses to determine the independent predictive value of each parameter, thereby optimizing model structure and diagnostic performance.

Conclusions

Cervical length, cervical volume and placental volume are independent risk factors for having PAS disease in patients with complete placenta previa with a history of cesarean delivery. According to the scoring system in this study, the higher the score, the higher the risk of having PAS disease in patients with complete placenta previa with a history of cesarean delivery. This scoring system has the potential to be applied to predict the likelihood of having PAS in patients with complete placenta previa with a history of cesarean delivery, thus contributing to the prenatal selection of rational treatment.

Abbreviations

PAS, placental implantation spectrum; MRI, magnetic resonance imaging; FIGO, International Federation of Gynecology and Obstetrics; DICOM, digital imaging and communications in medicine; PPV, positive predictive value; NPV, negative predictive value; ROC, receiver operating characteristic; BMI, body mass index; NICU, neonatal intensive care unit; OR, odds ratio; PP, placenta previa; CS, caesarean section; MAP, morbidly adherent placenta; IS-AIP, International Society for Abnormal Invasive Placenta; CL, cervical length; CV, cervical volume; PV, placental volume; PA, placenta accreta.

Data Sharing Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Ethics Approval and Consent to Participate

This study was reviewed by the Ethics Committee of Suzhou Hospital of Nanjing Medical University (Approval K-2022-015-K01). Informed consent was waived because this anonymously selected study was retrospective and no new interventions were performed on patients.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This study was supported by SuZhou Gusu Medical Youth Talent (grant number GSWS2023055), Suzhou Science and Technology Development Plan (grant number SYW2025052) and Suqian Science and Technology Plan Research Project (grant number SY202210).

Disclosure

The authors declare no competing interests in this work.

References

1. Jauniaux E, Aplin JD, Fox KA, et al. Placenta accreta spectrum. Nature Reviews Disease Primers. 2025;11(1):40. doi:10.1038/s41572-025-00624-3

2. Liu X, Wang Y, Wu Y, et al. What we know about placenta accreta spectrum (PAS). Eur J Obstet Gynecol Reprod Biol. 2021;259:81–89. doi:10.1016/j.ejogrb.2021.02.001

3. Silver RM, Branch DW. Placenta accreta spectrum. N Engl J Med. 2018;378(16):1529–1536. doi:10.1056/NEJMcp1709324

4. Wu X, Yang H, Yu X, et al. The prenatal diagnostic indicators of placenta accreta spectrum disorders. Heliyon. 2023;9(5):e16241. doi:10.1016/j.heliyon.2023.e16241

5. Maurea S, Verde F, Romeo V, et al. Prediction of placenta accreta spectrum in patients with placenta previa using a clinical, US and MRI combined model: a retrospective study with external validation. Eur J Radiol. 2023;168:111116. doi:10.1016/j.ejrad.2023.111116

6. Delli Pizzi A, Tavoletta A, Narciso R, et al. Prenatal planning of placenta previa: diagnostic accuracy of a novel MRI-based prediction model for placenta accreta spectrum (PAS) and clinical outcome. Abdom Radiol. 2019;44(5):1873–1882. doi:10.1007/s00261-018-1882-8

7. Yue Y, Zhu L, Liu C, et al. The relationship between cervical length and area measurements evaluated by MRI and the amount of hemorrhage in PAS cases. BMC Pregnancy Childbirth. 2024;24(1):293. doi:10.1186/s12884-024-06472-5

8. Yue Y, Song Y, Zhu L, et al. The MRI estimations of placental volume, T2 dark band volume, and cervical length correlate with massive hemorrhage in patients with placenta accreta spectrum disorders. Abdom Radiol. 2024;49(7):2525–2533. doi:10.1007/s00261-024-04272-1

9. Thurn L, Lindqvist PG, Jakobsson M, et al. Abnormally invasive placenta-prevalence, risk factors and antenatal suspicion: results from a large population-based pregnancy cohort study in the Nordic countries. BJOG. 2016;123(8):1348–1355. doi:10.1111/1471-0528.13547

10. Saxena U, Rana M, Tripathi S, et al. Prediction of placenta accreta spectrum by prenatal ultrasound staging system in women with placenta previa with scarred uterus. J Obstet Gynaecol India. 2023;73(Suppl 2):191–198. doi:10.1007/s13224-023-01830-3

11. Marshall NE, Fu R, Guise JM. Impact of multiple cesarean deliveries on maternal morbidity: a systematic review. Am J Obstet Gynecol. 2011;205(3):262.e1–8. doi:10.1016/j.ajog.2011.06.035

12. Morel O, Collins SL, Uzan-Augui J, et al. A proposal for standardized magnetic resonance imaging (MRI) descriptors of abnormally invasive placenta (AIP) – from the international society for AIP. Diagn Interv Imaging. 2019;100(6):319–325. doi:10.1016/j.diii.2019.02.004

13. Carusi DA, Duzyj CM, Hecht JL, et al. Knowledge gaps in placenta accreta spectrum. Am J Perinatol. 2023;40(9):962–969. doi:10.1055/s-0043-1761635

14. Erfani H, Fox KA, Clark SL, et al. Maternal outcomes in unexpected placenta accreta spectrum disorders: single-center experience with a multidisciplinary team. Am J Clin Exp Obstet Gynecol. 2019;221(4):337.e1–337.e5. doi:10.1016/j.ajog.2019.05.035

15. Yu FNY, Leung KY. Antenatal diagnosis of placenta accreta spectrum (PAS) disorders. Best Pract Res Clin Obstetrics Gynaecol. 2021;72:13–24.

16. Silver RM, Fox KA, Barton JR, et al. Center of excellence for placenta accreta. Am J Obstet Gynecol. 2015;212(5):561–568. doi:10.1016/j.ajog.2014.11.018

17. Zou L, Wang P, Song Z, et al. Effectiveness of a fetal magnetic resonance imaging scoring system for predicting the prognosis of pernicious placenta previa: a retrospective study. Front Physiol. 2022;13:921273. doi:10.3389/fphys.2022.921273

18. Tovbin J, Melcer Y, Shor S, et al. Prediction of morbidly adherent placenta using a scoring system. Ultrasound Obstet Gynecol. 2016;48(4):504–510. doi:10.1002/uog.15813

19. Kingdom JC, Hobson SR, Murji A, et al. Minimizing surgical blood loss at cesarean hysterectomy for placenta previa with evidence of placenta increta or placenta percreta: the state of play in 2020. Am J Clin Exp Obstet Gynecol. 2020;223(3):322–329. doi:10.1016/j.ajog.2020.01.044

20. Etori Y, Nagai R, Shimomoto Y, et al. Successful management of first-trimester uterine rupture and placenta previa: a case report. Cureus. 2025;17(1):e77857. doi:10.7759/cureus.77857

21. Yue Y, Wang X, Zhu L, et al. Placental volume as a novel sign for identifying placenta accreta spectrum in pregnancies with complete placenta previa. BMC Pregnancy Childbirth. 2024;24(1):52. doi:10.1186/s12884-024-06247-y

The Communications Regulatory Authority of Namibia (CRAN) has granted authorisation to Blue Telecommunications (Pty) Ltd, a subsidiary operating under Radio Electronic (Pty) Ltd’s license, to roll out Eutelsat OneWeb connectivity solutions nationwide. Operating from Low Earth Orbit, Eutelsat OneWeb’s satellite constellation provides high-speed, low-latency internet connectivity tailored for regions with inadequate or nonexistent ground-based network infrastructure. The service primarily serves sectors including enterprises, governmental institutions, maritime operations, aviation, and essential infrastructure providers.

Francois du Toit, Chief Executive Officer of Radio Electronic, said the approval marked a significant milestone for both the company and the country.

“This is a proud moment for Radio Electronic and for Namibia. Securing regulatory approval enables us to introduce Eutelsat OneWeb’s advanced LEO connectivity to the country for the first time,” du Toit said.

Du Toit stressed that LEO technology should be viewed as complementary rather than disruptive, stating it’s not a replacement for fibre, mobile or fixed wireless networks, but as an additional layer of infrastructure aimed at improving coverage, resilience and performance.

Laying the Groundwork for LEO Connectivity in Namibia

Namibia’s LEO connectivity landscape is at an early but consequential stage, shaped by a regulatory approval that reflects the strength of the country’s telecommunications framework. The authorisation granted to Radio Electronic positions it as Namibia’s first locally licensed provider of LEO satellite services, enabling advanced global satellite technologies to enter the market through a regulated, locally anchored operating model.

While the approval represents a historic milestone, full service activation remains subject to the completion of outstanding administrative steps, notably the formal issuance of the physical licence by CRAN, despite type approvals for the required hardware already being in place. Strategically, the rollout aligns closely with CRAN’s national objectives to deliver secure, reliable, and compliant connectivity solutions, particularly for enterprise, government, and other mission-critical users, reinforcing LEO satellite services as an increasingly integral component of Namibia’s digital infrastructure landscape.

Alongside this initial market entry, recent developments involving Starlink are further defining Namibia’s LEO connectivity environment, with the company entering a public consultation phase as part of its regulatory engagement process. During the consultation, Starlink received public support for its proposed operations in the country, reflecting interest in expanded satellite-based connectivity and broader awareness of LEO services among local stakeholders.

Empowering industrial teams to connect legacy equipment, collect actionable data, and visualize insights in real time. 

HOFFMAN ESTATES, Ill., Jan. 19, 2026 /PRNewswire/ — Omron Automation has released the DX100 Data Flow Edge Device, an industrial edge solution designed to connect directly to existing PLCs, sensors, and other automation devices. DX100 enables manufacturers to securely connects, collects, formats, and shares data intuitively. Without modifying current control logic or requiring extensive programming experience. 

DX100 is a single, industrial data edge device that supports a broad range of industrial protocols. It standardizes data at the source and delivers it to higher-level systems in a consistent, repeatable way, accelerating digital transformation initiative across the factory floor. 

• Industrial connectivity to existing machines: Collect data from installed equipment without modifying or replacing current control systems.
• SpeeDBee Synapse low-code environment: Low-code flow chart design with prebuilt collectors enables faster deployment by users with varying skill levels.
• Flexible development platform for custom logic: An easy-to-use environment supporting Python that allows teams to build and deploy tailored data processing logic.
• Built-in support for production dashboards: With Grafana built-in, the single unit can host a wide range of dashboards, delivering visualizations as unique as the data being collected.
• Standard northbound interfaces to cloud systems: Collect data over MQTT, and SQL, then share the consolidated data over MQTT to maximize network bandwidth.
• Predictable licensing for scalable deployments: Transparent, device-based licensing helps control costs as systems expand across multiple lines or facilities. 

Learn More: https://omron.pub/4pGJDY0

About Omron Automation 

Omron Automation is an industrial automation partner that creates, sells, and services fully integrated automation solutions that include sensing, control, safety, vision, motion, and more. Established in 1933, OMRON helps businesses solve problems with creativity in more than 110 countries. Visit https://automation.omron.com/en/us/

SOURCE Omron Automation Americas