New Estimates of US Civil War mortality from full-census records.

The Civil War was the deadliest conflict in US history. However, incomplete records have made it difficult to estimate the exact death toll both nationally, and especially, at the state level. In this article, we leverage the recently released full count of individual census returns and a sample of linked records across multiple censuses to provide i) the most precise national estimate of excess mortality to date and ii) reliable state-level estimates of excess mortality among native-born white males.

Targeting colorectal cancer with Herba Patriniae and Coix seed: Network pharmacology, molecular docking, and validation.

Background: Herba Patriniae and Coix seed (HC) constitute a widely utilized drug combination in the clinical management of colorectal cancer (CRC) that is known for its diuretic, anti-inflammatory, and swelling-reducing properties. Although its efficacy has been demonstrated in a clinical setting, the active compounds and their mechanisms of action in CRC treatment remain to be fully elucidated.

Aim: To identify the active, CRC-targeting components of HC and to elucidate the mechanisms of action involved.

A Porphyrin-Faced ZnL Cage for Selective Oxidation of C(sp)-H Bonds and Sulfides.

Catalytic oxidation of benzyl C-H bonds and sulfides from fuel oils stands as an attractive proposition in the quest for clean energy, yet their simultaneous oxidation with a singular, economically friendly catalyst is not well established. In this work, the combination of a cobalt(II) porphyrin ligand with 2-pyridinecarboxaldehyde and Zn yielded a ZnL cage (Co cube). The three-dimensional conjugated structure effectively enhances energy transfer efficiency, enabling the Co cube to show a good ability to activate oxygen under light conditions for photooxidation.

Deep learning-based workflow for hip joint morphometric parameter measurement from CT images.

Precise hip joint morphometry measurement from CT images is crucial for successful preoperative arthroplasty planning and biomechanical simulations. Although deep learning approaches have been applied to clinical bone surgery planning, there is still a lack of relevant research on quantifying hip joint morphometric parameters from CT images.This paper proposes a deep learning workflow for CT-based hip morphometry measurement.

Two-stage multi-task deep learning framework for simultaneous pelvic bone segmentation and landmark detection from CT images.

Purpose: Pelvic bone segmentation and landmark definition from computed tomography (CT) images are prerequisite steps for the preoperative planning of total hip arthroplasty. In clinical applications, the diseased pelvic anatomy usually degrades the accuracies of bone segmentation and landmark detection, leading to improper surgery planning and potential operative complications.

Methods: This work proposes a two-stage multi-task algorithm to improve the accuracy of pelvic bone segmentation and landmark detection, especially for the diseased cases.

Self-registration of constant-step rotating Mueller matrix polarimeters.

Time-division framework is commonly used in Mueller matrix polarimeters (MPs), which takes extra numbers of images at the same position in an acquisition sequence. In this Letter, we utilize measurement redundancy to raise a unique loss function which can reflect and evaluate the degree of mis-registration of Mueller matrix (MM) polarimetric images. Further, we demonstrate that the constant-step rotating MPs have a self-registration loss function free from systematic errors.

A Dual-Modality Imaging Method Based on Polarimetry and Second Harmonic Generation for Characterization and Evaluation of Skin Tissue Structures.

The characterization and evaluation of skin tissue structures are crucial for dermatological applications. Recently, Mueller matrix polarimetry and second harmonic generation microscopy have been widely used in skin tissue imaging due to their unique advantages. However, the features of layered skin tissue structures are too complicated to use a single imaging modality for achieving a comprehensive evaluation.

A Smartphone-Based Biosensor for Non-Invasive Monitoring of Total Hemoglobin Concentration in Humans with High Accuracy.

In this paper, we propose a smartphone-based biosensor for detecting human total hemoglobin concentration in vivo with high accuracy. Compared to the existing biosensors used to measure hemoglobin concentration, the smartphone-based sensor utilizes the camera, memory, and computing power of the phone. Thus, the cost is largely reduced.

Cloning southern corn rust resistant gene RppK and its cognate gene AvrRppK from Puccinia polysora.

Broad-spectrum resistance has great values for crop breeding. However, its mechanisms are largely unknown. Here, we report the cloning of a maize NLR gene, RppK, for resistance against southern corn rust (SCR) and its cognate Avr gene, AvrRppK, from Puccinia polysora (the causal pathogen of SCR).

Analyzing the Influence of Imaging Resolution on Polarization Properties of Scattering Media Obtained From Mueller Matrix.

The Mueller matrix contains abundant micro- and even nanostructural information of media. Especially, it can be used as a powerful tool to characterize anisotropic structures quantitatively, such as the particle size, density, and orientation information of fibers in the sample. Compared with unpolarized microscopic imaging techniques, Mueller matrix microscopy can also obtain some essential structural information about the sample from the derived parameters images at low resolution.

Population-specific brain [F]-FDG PET templates of Chinese subjects for statistical parametric mapping.

Statistical Parametric Mapping (SPM) is a computational approach for analysing functional brain images like Positron Emission Tomography (PET). When performing SPM analysis for different patient populations, brain PET template images representing population-specific brain morphometry and metabolism features are helpful. However, most currently available brain PET templates were constructed using the Caucasian data.

regBase: whole genome base-wise aggregation and functional prediction for human non-coding regulatory variants.

Predicting the functional or pathogenic regulatory variants in the human non-coding genome facilitates the interpretation of disease causation. While numerous prediction methods are available, their performance is inconsistent or restricted to specific tasks, which raises the demand of developing comprehensive integration for those methods. Here, we compile whole genome base-wise aggregations, regBase, that incorporate largest prediction scores.

Long-term follow-up after laparoscopic versus open distal gastrectomy for advanced gastric cancer.

This study aimed to compare the long-term outcomes of laparoscopic and open distal gastrectomy for advanced gastric cancer. Between January 2007 and December 2014, patients with advanced gastric cancer underwent distal gastrectomy by laparoscopic or open approach were identified. Patients in both groups were selected after being matched by age, gender, American Society of Anesthesiologists (ASA) class and clinical TNM stage using propensity score method, to create two comparable groups: laparoscopy and open groups, and prognosis were compared between these two groups.

Stem cell-like circulating tumor cells indicate poor prognosis in gastric cancer.

Circulating tumor cells (CTCs), which have stem cell-like characteristics, might play a crucial role in cancer metastasis. CD44 has been identified as gastric cancer (GC) stem cell (CSC) marker. Here, the prognostic significance of CD44-positive CTCs in GC patients was investigated.