PLOS ONE Alerts: New Articles

1. Correction: Assessing the impact of digital transformation on capital market information efficiency under environmental uncertainty: Evidence from China

   by Tao Feng, Xiaohuan Dong, Yueyun Wang

2. The impact of baseline laboratory tests on the management of new-onset hypertension in primary care: A pilot study

   by Katia Kteich, Maria R. Karam, Marouan Zoghbi, Mabel Aoun

   Background

   Hypertension is a key contributor to the global cardiovascular disease burden. In 2021, the World Health Organization (WHO) hypertension management guideline suggested baseline laboratory tests for patients with newly diagnosed hypertension but noted limited evidence in primary care contexts. This study evaluates the impact of baseline laboratory assessments on blood pressure control and comorbidities in newly diagnosed hypertensive patients.

   Methods

   This is a multicenter retrospective study that included all patients with new-onset hypertension between January 2015 and January 2020, followed in three primary health care centers until 2022. Data collection included 8 items of paraclinical tests performed at the diagnosis of hypertension: serum sodium, potassium and creatinine, lipid panel, electrocardiogram, glucose, HbA1c and urine dipstick. Complete workup was defined as having the 8 items checked and partial workup included 1–7 items. Blood pressure was assessed at one year and the final visit, which was beyond one year, in the two workup groups.

   Results

   Of 621 hypertensive patients, 107 with incident hypertension were analyzed (mean age: 54.8 ± 12.7 years; 58.9% women). A complete workup was done for 48 patients, partial for 52 and none for 7. Abnormalities detected included: 8.4% of patients with fasting blood glucose > 125 mg/dL, 7.5% with HbA1c > 6.5%, 1.9% with serum potassium < 3.5 mmoL/L, 54.2% with LDL Cholesterol > 100 mg/dL, 35.5% with serum creatinine > 0.8 mg/dL, and 7.5% with an estimated GFR < 60 mL/min/1.73 m2. Significant systolic blood pressure improvement was seen at 12 months in the complete workup group (129.9 ± 13.6 mmHg) vs. partial workup group (142.8 ± 18.9 mm Hg) (P = 0.003). Men and smokers were tested more often than women and non-smokers.

   Conclusion

   Baseline laboratory tests in patients with newly diagnosed hypertension help unmask comorbidities such as chronic kidney disease, diabetes, and dyslipidemia. Our findings support the use of baseline laboratory testing in order to optimize blood pressure control and individual patient management.

3. Correction: ECP-IEM: Enhancing seasonal crop productivity with deep integrated models

   by Ghulam Mustafa, Muhammad Ali Moazzam, Asif Nawaz, Tariq Ali, Deema Mohammed Alsekait, Ahmed Saleh Alattas, Diaa Salama AbdElminaam

4. DEFIF-Net: A lightweight dual-encoding feature interaction fusion network for medical image segmentation

   by Zhanlin Ji, Shengnan Hao, Quanming Zhao, Zidong Yu, Hongjiu Liu, Lei Li, Ivan Ganchev

   Medical image segmentation plays a crucial role in computer-aided diagnosis. By segmenting pathological tissues in medical images, doctors can observe anatomical structures more clearly, thereby achieving more accurate disease diagnoses. However, existing medical image segmentation networks have issues such as insufficient capability to extract features from target areas, as well as high number of parameters and increased computational complexity. To address these issues, a lightweight Dual-Encoding Feature Interaction Fusion network (DEFIF-Net) is proposed in this paper for medical image segmentation. Firstly, in the encoding stage of DEFIF-Net, a global dependency fusion branch is introduced as an additional encoder to capture distant feature dependencies, whereby the neighboring and distant feature dependencies are effectively integrated by the newly designed feature interaction fusion convolution. Secondly, between the encoder and decoder, channel feature reconstruction modules (CFRMs) are used to enhance the feature representation of important channels. Additionally, a novel multi-branch ghost module (MBGM) is used in the bottleneck layer of the network to enhance its efficiency in capturing and retaining different types of feature information. Lastly, a novel residual feature enhancement (RFE) decoder is utilized to emphasize boundary features, thereby increasing the network’s sensitivity to lesion boundaries. The segmentation performance of the proposed DEFIF-Net network is evaluated in two different medical image segmentation tasks. The obtained experimental results demonstrate that, compared to state-of-the-art networks, DEFIF-Net exhibits superior segmentation performance on all three datasets used, while also having a lower parameter count and computational complexity.
5. Correction: Attitudes, practices, and zoonoses awareness of community members involved in the bushmeat trade near Murchison Falls National Park, northern Uganda

   by BreeAnna M. Dell, Marcy J. Souza, Adam S. Willcox