class Graph:

    def __init__(self, n, directed=False, decrement=True, edges=[]):
        self.n = n
        self.directed = directed
        self.decrement = decrement
        self.edges = [[] for _ in range(self.n)]
        for x, y, cost in edges:
            self.add_edge(x, y, cost)

    def add_edge(self, x, y, cost):
        if self.decrement:
            x -= 1
            y -= 1
        self.edges[x].append((y, cost))
        if self.directed == False:
            self.edges[y].append((x, cost))

    def dijkstra(self, start=None, INF=10**18):
        """
        返り値は 0-indexed !!!
        :param start: スタート地点
        :return: スタート地点から各点への距離のリスト
        備考: heqpq の比較のための key は第一引数である点に注意( = heappush(heapq, (key,value)) )
        """
        self.parent=parent=[-1]*N
        res = [INF] * self.n
        if start is None: start=self.decrement
        start=start-self.decrement
        res[start] = 0
        next_set = [(0, start)]
        while next_set:
            dist, p = heappop(next_set)
            if res[p] < dist:
                continue
            """ここで頂点pまでの最短距離が確定。よって、ここを通るのはN回のみ"""
            for q, cost in self.edges[p]:
                temp_d = dist + cost
                if temp_d < res[q]:
                    res[q] = temp_d
                    parent[q] = p
                    heappush(next_set, (temp_d, q))

        return res

    def path_restoring(self,start,goal):
        start,goal=start-self.decrement,goal-self.decrement
        q=goal
        res=[]
        while q!=start:
            res.append(q+self.decrement)
            q=self.parent[q]
            if q<0: return -1
        res.append(start+self.decrement)
        return res[::-1]


    def draw(self):
        """
        :return: グラフを可視化
        """
        import matplotlib.pyplot as plt
        import networkx as nx

        if self.directed:
            G = nx.DiGraph()
        else:
            G = nx.Graph()
        for x in range(self.n):
            for y, cost in self.edges[x]:
                G.add_edge(x + self.decrement, y + self.decrement, weight=cost)


        edge_labels = {(i, j): w['weight'] for i, j, w in G.edges(data=True)}
        pos = nx.spring_layout(G)
        nx.draw_networkx(G, pos, with_labels=True, connectionstyle='arc3, rad = 0.1')
        nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels)
        plt.axis("off")
        plt.show()

#########################################################
def example():
    global input
    example = iter(
        """
3 3
1 2 1
1 3 1
2 3 3
        """
            .strip().split("\n"))
    input = lambda: next(example)

def example2():
    global input
    example = iter(
        """
6 9
1 2 7
2 3 10
1 3 9
1 6 14
3 6 2
5 6 9
4 5 6
2 4 15
3 4 11
        """
            .strip().split("\n"))
    input = lambda: next(example)

#########################################################
import sys
from heapq import *
input = sys.stdin.readline

# example2()

INF = 10**18  # 大きい数字

N, M = map(int, input().split())
graph = Graph(N, directed=False, decrement=True)

data=[]

for _ in range(M):
    x, y, cost, cost2 = map(int, input().split())
    graph.add_edge(x, y, cost)
    data.append((x,y,cost,cost2))

dist = graph.dijkstra(start=1,INF=INF)
path=graph.path_restoring(1,N)

used=set()

for i in range(len(path)-1):
    used.add((path[i],path[i+1]))
    used.add((path[i+1],path[i]))

graph2 = Graph(N, directed=False, decrement=True)

for x, y, cost, cost2 in data:
    if (x,y) in used:
        graph2.add_edge(x, y, cost2)
    else:
        graph2.add_edge(x, y, cost)

dist2 = graph2.dijkstra(start=1,INF=INF)

print(dist[-1]+dist2[-1])